Simbiosis

simbiosis

Artificial intelligence and blockchain are trending technologies that are improving business models and transforming entire industries. Deloitte refers to them as the most exciting trends of 2022, and Gartner their rapid development for decades to come. predicts Don Tapscott, Blockchain Research Institute founder, talks about the possible merging of blockchain, AI, and the Internet in a trivergence. This trivergence will be the basis of the second era of the digital age, where blockchain will record and protect data as AI will analyze it. Let's take a look at how blockchain and AI can work together. An Excursion into AI and Blockchain Technology Many people consider distributed ledger technology, or blockchain, to be synonymous with cryptocurrency. This isn't the case, as cryptocurrency - while being the most popular - is just one of the many ways that blockchain technology can be harnessed. A blockchain database is distributed over blocks linked together in a chain. Entries in a block are hashed so that no one can change or delete the information. For transactions to be carried out honestly, a consensus mechanism works in the network when blockchain participants confirm or reject unauthorized actions. These features are adopted by industries to prevent fraud, protect information, and/or manage business-critical transactions. AI, on the other hand, is a set of deep and machine learning algorithms that mimic human thought. AI processes and arranges volumes of data that are beyond the extent of human capabilities. Furthermore, AI takes the burden off people by automating routine manual operations. For enterprises, it is becoming a business intelligence tool or a mechanism for protecting against cyber-attacks. AI can be applied to everything from writing articles for the Associated Press to early detection of diseases. Since AI and blockchain are not related in any way, how then can they work together? Understanding the Connection between Blockchain and AI Despite the dissimilarity between the two technologies, they can be used to complement each other and eliminate each other's shortcomings. Thus, blockchain will create more trust in AI platforms, maintaining security and privacy. AI will strengthen the protection of transactions, and contribute to the monetization of information. Blockchain will also clarify the work of AI by recording in detail the data on which decisions made by smart algorithms are based. AI, in turn, can support the scalability of blockchain applications by automating the management procedures of a decentralized network. It allows businesses to collect, analyze and apply the data received, while blockchain allows them to check, record, and perform certain actions with them. AI and blockchain are like the yin-yang of the digital world, providing businesses with the missing harmony. , CEO of Walnut, these technologies enhance each other, and entrepreneurs should explore their implementation options to gain a deeper understanding of business. According to Yoav Vilner 4 Instances of a Beneficial Relationship between Blockchain and AI The convergence of blockchain and AI opens up many new business opportunities. Let's look at promising use cases of this powerful combination of technologies. 1. Enhanced data protection mechanism Blockchain is considered synonymous with security because every block in a chain is encrypted with a hash algorithm. It is almost impossible to decrypt the data because a unique key is created for each block. In addition, this key changes when a new block is added to the chain. A user has a personal key to access information and a public key to conduct transactions. Despite such multi-layered protection, vulnerabilities can be found in blockchain-related applications. Take, for example, the DAO , when the company lost over 3.6 million ether, or the on the Bitfinex cryptocurrency exchange when an amount of 119,000 Bitcoin was stolen. hack attack AI strengthens the existing blockchain security mechanism, bringing the risks of attacks to a minimum. A smart algorithm analyzes anomalies in the blockchain, and in the future, it will learn how to work with encrypted data. It will analyze arrays of protected data and find potential bottlenecks so that developers can deal with them. For example, say a person invests a fixed amount of money in EFT every month. Suddenly, an investment exceeds the usual sum by 10 times. AI evaluates such a transaction as suspicious, and an anti-fraud mechanism is triggered to stop anomalous activities in time. 2. Validation of decision-making process by AI algorithm Explainability is one of the unresolved issues that is hindering the widespread adoption of AI. It is difficult for people to rely on AI when they do not understand why a certain solution is proposed. For greater confidence, people need the logical validity of the proposals put forward by AI. , a method elaborated by scientists to increase the transparency of AI, and attention techniques are still far from ideal and are still being developed. Blockchain claims to be the third and more justified solution to the problem of explainability of AI. LIME Blockchain can make the secret and the incomprehensible in the work of AI transparent and explainable. The distributed database stores each decision made by AI in blocks so that the user can view and analyze it. At the same time, decentralization and enhanced encryption of the registry ensures that information is protected from unauthorized access. When people begin to understand how the decision-making mechanism of AI works, they will trust the technology more. This, in turn, will accelerate the pace of implementation of AI in healthcare, fintech, logistics, and other areas of human activity. Such a move towards transparency would make AI-powered blockchain medical applications a common practice. Logistics companies will launch blockchain and AI-based infrastructure to monitor the supply chain in real-time. Cadastral companies, like Sweden's , will use blockchain and AI to store and track documents for property sales. Lantmäteriet Soon, blockchain and AI might be able to comply with the conditions of the GDPR specified in Article 22 and WP29. A person will receive an explanation of decisions and with it the right to accept or challenge them to control AI. 3. Improved data control and monetization The volume of data generated by mankind is growing rapidly and, , will increase from 64 zettabytes in 2020 to 180 zettabytes in 2025. Such a large stream of data needs to be processed, analyzed, and stored securely, providing access only to the owners. according to Statista experts The data that businesses collect may relate to individual customers, suppliers, and products. They also need to be correctly extracted and researched to be used for critical business processes, key business forecasts, and fundamental decisions for development. AI takes over this function by working with data in a decentralized secure network. At the same time, the convergence of AI and blockchain makes possible a new type of income - the monetization of personal data. An owner can store personal information in a decentralized network and sell it to interested parties: research organizations, medical institutions, and other companies. For a certain amount, a user can open temporary access to personal data. Information-selling platforms like are creating a marketplace for data that can be used for business purposes. Hu-manity.co Each organization will be able to leverage the convergence of AI and blockchain in different ways, depending on the goals and type of underlying data. Firms that are first to adopt these technologies will see immediate results and gain an edge over companies that are just starting to introduce innovations. 4. Reducing power consumption when mining To keep the Internet running, servers need to be operating 24 hours a day, 365 days a year. They need a constant flow of electricity - about 1% of the world's supply, and most of it goes to cool data centers. that maintaining the Internet can cause 0.3% of global CO2 emissions. Planetly estimates Tech giants began to look for ways to reduce the negative impact on the environment. So, Google has been using the DeepMind algorithm to manage the data center for more than 5 years. Trained on an array of historical data, the neural network “knows” how to rationally use the cooling system. As a result, Google managed to energy consumption by 40%. reduce A similar control mechanism can be introduced into the mining process to cool large data centers. AI in this case will not only reduce environmental pollution but also lead to lower prices for mining hardware. Conclusion The four AI and blockchain use cases mentioned above are not just theories. Organizations possible ways to apply technologies in a single project. As smart algorithms and decentralized ledgers improve, it will be possible to implement profitable business solutions. are testing AI needs blockchain to show how a smart algorithm works. Blockchain benefits from stronger AI defenses, better smart contracts, and lower power consumption. Soon, we will surely witness discoveries related to the joint use of AI and blockchain. The reality that seemed fantasy is approaching.

Blockchain - AI Symbiosis and the Future of the Digital Age

Photo by on . Tom Dahm Unsplash The classic human error is assuming we’re doing a good job, because we have nothing better to compare ourselves to. Humans operate with small data sets and execute flawed analytical reports. Machines operate with far larger ones and are capable of carrying out advanced analysis, achieving far more accurate results. Thus, for example, far too often, we’ll see someone go to a certain college, get a certain degree, and then have a successful career and assume it will work for us as well. But in practice, our conclusion may be flawed, due to a number of reasons. Namely, humans can only contain and analyze a limited amount of data. Moreover, we aren’t always able to execute advanced analysis and remove bias, often leading us to skewed results or a failure to separate between correlation and causation. In the context of AI transformations, employees often don't see the urgent need for improving their workflow, because they are only seeing the data-context they have in front of them, not all the data they are missing, or, the larger data-context. In other words, the exponential creation rate of data, along with its natural vastness, mean that we can be so far behind, we aren't even capable of recognizing what we are missing. Lingering Negative Data-Habits: Analysts are inherently forced to filter out large amounts of data based on generic axioms because the alternative requires the analyst to work with an impossible amount of data. While the advantage of having a small data set is that the analyst can perform higher quality manual analysis, he often loses out on lots of information from the data he excludes. But the damage is greater than just that. Other than just missing out on specific data-points of value, the analyst may become unaware of full segments of data that have value, due to false assumptions. This creates an endless loop where in each subsequent tasks, the analyst continues to falsely pre-determine his segments based on past (unreliable) experiences and results, thus creating a fatal downwards spiral. This often nurtures a false sense of certainty as to the validity of the results with no substantial way of knowing what is falling between the cracks. Organizations end up with an over-developed sense of confidence in their data and draw conclusions which are only true for the small data-context they have in front of them. Similarly, as humans, analysts tend to be biased towards implementing filtration systems that output the data-set with the highest probability to contain value. This makes sense when there is no alternative to human-centric tasks. However, when we introduce machines into our workflow, it is critical to shake this underlying bias. If a machine is doing the work, purely from a business standpoint, the rate of non-valuable to valuable data-point is far less important. The only important metric becomes the net amount of valuable data alongside the cost of time required by any humans alongside the machine. In sum, Making machine-centric tasks more “humanly possible” in nature, is detrimental to our goals. Adjusting our Mindset for the age of Big Data: A human analyst may be able to segment data with 100% accuracy, while a machine may only be able to perform the same analysis with 85% accuracy after training. Despite that, what we, as humans, tend to ignore, is that 85% of 100X data which the machine is able to analyze may be more valuable and in fact, more accurate. Our initial response, as humans, tends to be opposing the use of the algorithm, thinking that only accurate results are of value. This is yet another human bias that needs to be removed once having introduced machines into a workflow.  Obviously, the quality of analysis is important, but when determining how to build a process, we need to remind ourselves that quantity actually creates higher quality. In other words, our instinctive definition of accuracy is skewed due to the small context in which we are seeing it. More importantly, casting a wide net of analysis on the larger data-set can provide a far more justified sense of confidence for organizations seeking credible conclusions. Creating a Symbiotic relationship between Humans and Machines: While the age where machines can do it all is not yet upon us, the age of human-machine teams has already arrived. There are many approaches to this, but to my mind, the most important success factor is building these systems in a manor that ensures that the value of each component’s work (human and machine) contributes to the other, symbiotically. For example, in a case where we require high quality data segmentation and analysis, a machine alone will likely fail us. However, having a machine segment data, with human in-depth review as a quality-control can solve this, allow for reviewing of more data, and in many cases, be more cost-effective than using a human analyst alone. Alternatively, even if we don’t trust the machine to do any of the data analysis, we can allow it to guide us in selecting the subset for human segmentation. Ironically, today, our first and most dangerous filtration is done by humans, usually not based on conclusive evidence. The key here is create systems that allow for the various elements of every task to be performed by the team component that is best suited for it. Leading Human Machine Teams: As managers and leaders, we have to train ourselves to look at the larger data context, and constantly suspect we are missing something. A failure to criticize, in this case, can be detrimental to an operation. None of this is to say that there is no place for human analysis, but rather, that human ability is far more effective when enriched with machine capabilities. We need to create human-machine analysis teams that work in conjunction with one another, not opposing one another. Looking ahead, it’s critical for managers to be able to separate between the role of the machine and the role of the human. Doing this well will allow humans and machines to work together, as “human-machine teams”, resulting in an outcome greater than it’s individual components. If in the past, one of the manager’s key responsibilities was to assign the most appropriate team member to every task, today, that role has expanded to include evaluating which part of each task should be human-centric, and which should be machine-centric. Those able to bridge the gap between the humanities-oriented task of putting these technologies into a human and business context with the technological know-how to guide their implementation, will be best positioned to lead a succesful transformation. We must always attempt to “know the unknowable”, even within our data. But the key to achieving that is first recognizing that our we all suffer from and in doing so, we can attempt to achieve human-machine symbiosis that will transform an operation. data-tunnel-vision

Avoiding Data-Tunnel-Vision and Achieving Human-Machine Symbiosis

Symbiosis. The more complex the ecosystem, the more nuanced the relationships. All organic life depends on the broader ecosystem for food, energy, survival, and reproduction. Our species is no different. It flourishes when we harness the flow of energy that derives from cooperation. Our civilization depends on the strength of our communities. We need each other to survive and thrive. In the same way that evolutionary biology teaches us that rich organic life ecosystems depend on symbiotic relationships, the space industry requires sustained and engaged networks over time. No single space mission or space business initiative operates as a stand-alone. Space research, travel, and exploration challenge us like no other industry. For several years now, there is a lot of enthusiasm and passion in the space industry. The newspace movement in this regard seeks to open up the business of space to new players in the private sector and advocate for increased public-private alliances. I have met numerous brilliant professionals in these newspace communities. From different backgrounds and with unique journeys, many shatter the myth of an ideal career path to the space sector. For the record, there is none. There are a variety of talent stacks across disciplines and businesses. I have wanted to write an article for some time now about some of these professionals. I had the opportunity to connect with three recently. These are some snippets of wisdom about their personal stories. In their voices, read how they work to build thriving communities in the industry. Bianca is a rocket scientist. She is also the current Director of International Business Development & Marketing at Carbice Corporation and Founding Director of Cosmica Space Consulting Ltd. Originally from Naples (Italy), Bianca has been based in the United Kingdom for several years now. She also serves as an advisor, speaker, and STEM ambassador for youth and women. Bianca Cefalo Bianca Cefalo. December 2020. The space bug I’m an accidental rocket scientist. My interest in engineering starts early on because my Dad used to work with cars. I liked what my Dad was doing with cars mainly spare parts and I enjoyed just staying in the garage. This is important because no one in my family had the sort of elite higher education. No one was an engineer. But being in Italy you get access to seeing a beautiful Ferrari and to see how it’s actually done. What is at the core of that piece of machine. Every Sunday I would watch Formula 1. I wouldn’t watch it as something that was male-dominated… I just loved seeing the competition, the teamwork, and how being high-tech is to go beyond the limits of what you see every day. The tipping point Specializing in aero and fluid dynamics engineering, I realized that I could join the beautiful color side of things with high-tech designs… How do you basically give life and colorful patterns to the air that is all around us and that we take for granted? That was my magic and my niche. Later, as I progressed in my studies, I realized that I could apply this entire specialization of fluid dynamics to aircraft and spacecraft, especially re-entry capsules and hypersonic vehicles. Then, when I saw the NASA/JPL InSight Mars Mission land in November 2018, after I had worked on one of the scientific instruments onboard the Lander, it went from starting just another job to understanding what my mission in the world is. Unlike generations before me, where people would start a project only to see it launch 20 years later, I helped build something that I saw landing on Mars. The more I kept studying, learning, and working, the more I understood how my work could impact humanity as a whole. Because how technologies advance in space, and as a consequence on Earth, changes how we communicate and evolve as a species. Mentors and guideposts I had to navigate mostly everything by myself. In many ways, this gave me a higher competitive edge because I had to make it happen on my own. I had to find the opportunities to get in. This was especially obvious being a woman. It motivated me even more... In retrospect, what I am doing right now and reaching out to young people and women evolves from the fact that I didn’t have that myself. To the young girls that I meet, talk, and listen to, I notice that some are frightened because they feel out of place. I tell them we feel out of place every day in the space industry. Every day there is a new challenge. Every day there is something that we haven’t seen before. Bianca Cefalo on Campus Media. November 2020. Community building and visions of possible futures I started creating a community, which I didn’t have before. I’m not just supporting the younger ones. I also feel encouraged to go to senior women who have been there for the past years and have a wealth of knowledge. I feel supported because I can actually share concerns and ask for advice about startups, venture capital, funding, etc. I would like to see more conversations and research about how to use more consciously our advancements in space. We will not be just talking about machines, rovers, robots going to space or leaving Earth. We will be talking about humans. How do we make sure that we don’t repeat the same mistakes on Earth, especially if a new species comes around. George is Co-Founder and Chief Space Economist at the . With deep expertise in the banking and financial sectors, George is also the Co-Host of the Space Economy Show at the Space Channel, a university professor, and a frequent speaker. He co-authored the book . This book is the first in the Space Economy Series. George Pullen Milky Way Economy Blockchain and the Space Economy George Pullen. December 2020. The space bug I grew up in a household in Maine (USA), where none of my parents were in the space industry. But we were immersed in space early on by following what NASA was doing, and also by tuning in to the cinema about space, Star Wars, Star Trek, Doctor Who, and so on… My parents' first date was going to watch Return of the Jedi. The tipping point For me, it always was about understanding how the markets were moving, what that movement would do to the larger economy, and what that meant for the profitable trading opportunities. This experience set me up for what I’m doing now. What I’m passionate about right now is the same alternative markets, what’s new, and what’s the future. We live in unique times. I believe we’re in the middle of the Fourth Industrial Revolution, where we see the convergence of technologies. Introduction to the Space Economy. George Pullen. February 2020. I see a lot of people talking about individual billionaires making big plays for their businesses or conversations around what NASA is doing and not necessarily from an economics or finance perspective. A potential road map for the business of space is to reach US$4 trillion in the next few decades… The idea of plugging into an industry that has the potential of having a 10x effect should be something that people pay attention to. That’s when I started talking with my partner and co-founder about outlining a book, TV show, and an educational platform that could plug this information into the larger community and spread the message… Mentors and guideposts My biggest mentor in finance and economics was one of my professors Dr. Robert A. Strong, CFA. He shared a background in the military like me. I saw what he did being a success on boards, in business, being an advisor, being a professor. I thought to myself that’s a roadmap for me. In terms of science and space, now more than ever we have access to all of people’s ideas in social networks and podcasts. I can track what’s going on and plug into these avatar mentors. Community building and visions of possible futures There’s a ton of people who love to watch these big launches. When those events capture the attention of millions of people, there’s a subsection that is not being engaged with. The lack of narrative going out to the community of supporters about what else is going on. Some businesses and startups are working on new technologies and tech transfer programs… You need a community that encourages others to start and that also supports it. There’s also a lack of narrative around the number of partnerships occurring in space. I am excited about putting out content that can be used as educational content. I want to frame it so that students can think of space as a business venture and not just as something that we can marvel at. I want people to understand and think of the business of space and how it relates to their future and their businesses and respective industries. I hope that my show reaches a lot of people that way. I’d like to see the community grow. Samson An anthropologist by training, is Co-Founder of the Milky Way Economy and Co-Host of the . Samson also co-authored the book with George. A university professor as well, Samson is a frequent speaker, advisor, and management consultant. Samson Williams Space Economy Show at the Space Channel Blockchain and the Space Economy Samson Williams. January 2021. The space bug I grew up in east Texas (USA) in the eighties in the middle of nowhere when you could still see the Milky Way. We didn’t have light pollution. I always wondered what was up there. I also grew up watching sci-fi, Battlestar Galactica, the Star Trek series, and the spin-offs, NextGen, Voyager, Deep Space Nine. Sci-fi can be an escape. When you can dream, you always want to get off Earth. Now, as an adult, I can go out and be part of the space economy. The tipping point I had been trying to calculate for some time what one pomegranate costs on Mars, just in the sense of cryptocurrency and blockchain. The Martian economy doesn’t run on dollars. It is a completely new system of value and money. In this new system, you’re going to need to use blockchain to encrypt those records of debt. Samson Williams on Bitcoin Live. December 2020. I went with George to the Air and Space Museum some time back. When you stand in front of a 100ft rocket, the space economy becomes a whole lot clear. I look at it from how you’re going to fund the space economy. You need money to get into space, particularly for small and medium-sized businesses. Otherwise, it’s just going to be dominated by the big guys SpaceX, Virgin Galactic, and Blue Origin. If you don’t have the smaller players helping build it, you don’t have an ecosystem. If you don't have an ecosystem, you don’t have a real economy. It's not sustainable. Mentors and guideposts I have met mentors along the way. You typically just need to listen. There are so many smart and incredible folks in the industry. My favorite person at the moment is Dr. Sian Proctor, also an analog astronaut. She often articulates the approach that when you solve for space, you solve for Earth. This approach is particularly important when you’re speaking with politicians and legislators. I talk to her on a semi-regular basis. Every time I talk with her, I learn something new. I represent Black people and Brown people in my work. When I go to meetings, it makes sense for me to articulate that we should have more diversity, inclusion, and representation in the rooms. It will make it a little easier for my nieces and nephews to go and open doors. Community building and visions of possible futures I also look at the space economy from the human perspective. Once you introduce the human element, space exploration gets nuanced. Rockets can pull whatever Gs the hardware can sustain, but humans blackout. For us to have a permanent settlement in the Moon, Mars, and beyond, it’s just not physics. It also involves human psychology. Probably the first quadrillionaire in space will be a she who masters the psychological aspects. We also need to be able to reproduce in space against a backdrop of radiation, cosmic rays, etc. As a species, we have evolved only on Earth. I want to see more women in space, particularly Black, Latino, and women of color. When they're represented and at the table, it's helpful for the space community and the space economy. Also, words matter. If you send a warrior to space, they’re there to fight. It’s a different sentiment if you send space explorers or sentinels. Right now, we’re gearing up to go to battle. We’re using the words. Our words have meanings. We need to change the way we articulate what humans do in space. Our futures in space depends on the strength of our community-building More than our abilities to imagine, create, and build cutting-edge technologies, what distinguishes us from other species is the ability to envision and co-create the futures we want. The space industry requires us to think beyond our comfort zones and any perceived limitations. Bianca, George, and Samson are some of the many professionals in the industry that actively build a sense of community in their distinctive ways. George and Samson often seek partnerships with universities, community colleges, and technical colleges to raise awareness and visibility about future vocations needed in space. Bianca also makes it a point to visit schools and educational centers often and connect with organizations overseas as a STEM ambassador. By conducting workshops and actively engaging with different people across sectors, all tackle fears and stereotypes head-on. Our futures in space and on Earth depend on the strength of our bonds. Nobody arrives alone. The energy in robust and engaged communities is precious. Community-building can serve as a resource among people who wouldn’t have otherwise considered entering the space industry. If you’re in the space industry, remember to continue to open doors and help build ladders. If you’re reading this and want to break in, don’t ask permission. We need the most cooperation and energy that we can harness to become a multi-planetary species. // Credits for the artwork featured at the top banner and throughout the article: (Domenico Barra & Luigi Console, Italy). Images are courtesy of the Leo Kuelbs Collection. OUR JOURNEY (2015) – MIGHTY_KONGBOT Born and raised in Naples, is a prolific and self-taught artist specialized in new digital media and glitch art. Domenico has exhibited his work extensively in Europe, Asia, Latin America, and the United States since 2010. Some of his digital works are also part of decentralized curatorial projects on blockchain technologies. Domenico shared the following with me about his artwork. Domenico Barra Artists are nodes of a network of a community… The inspiration for this particular video comes from a fellow glitch artist, Nick Briz. Nick depicted the work of a glitch artist as that of an explorer. By trying to figure out and understand computers through their errors (glitches), glitch art is a journey in the ever-changing digital landscape… I wanted to visually portray what was my path through this journey as I became a glitch artist. I partnered with a friend to build this glitch landscape by experimenting with one of the most complex and popular satellite imagery software options, Google Earth. It was an opportunity to simulate a drone traveling on Earth and in space. This opportunity forced us to think beyond the software and the hardware.

Symbiosis: The Need For Stronger Communities in the Space Industry

While improvements in AI and Deep Learning move forward at an ever increasingly rapid rate, people have started to ask questions. Questions about jobs being made obsolete, questions about the inherent biases programmed into the neural networks, questions about whether or not AI will eventually consider humans as dead-weight and unnecessary to achieve the goals they've been tasked programmed with. And while those are valid questions, I believe there is an area of AI that has not received as much attention. An area which should be addressed as early as, like, right now. What are we doing to keep our AI algorithms safe from malicious attacks? I like to think about this problem using an analogy from the late 90's and early 2000's. Back in the day when dynamic websites were new we used to code database queries with no consideration about security until MySQL injections became the de-facto way of gaining access into a system. We are on the brink of literally trusting our lives with AI algorithms for the first time in history. Think self-driving cars. Tesla extremely close of deploying full self-driving cars at a massive scale. I'm certain that statistically the Tesla self-driving car will drive safer than the average human, but is Tesla "escaping" their self-driving algorithms? Are there vulnerabilities in their systems that could be exploited by malicious attackers and cause a tragic accident? Researchers are hard at work to understand how different neural networks  can be attacked and yield unexpected results. . This video from the YouTube channel Two Minute Papers is a true eye opener In short: changing 1 pixel in an image can be enough to mis-lead a neural network and make it yield results with are completely off. Although these so called "one pixel attacks" are not trivial to pull off (it takes a lot of analysis to figure out which pixel to change, and what color to set it to), it's not hard to extrapolate and wonder if current AI systems are vulnerable to these types of attacks, especially those in which we trust our lives with. No system is ever 100% safe so I think it's safe to assume any AI algorithm will have some degree of vulnerability that could potentially be exploited. And that begs the question: could someone exploit such a vulnerability (or a similar one) to cause real harm to human life? Are companies paying attention to these problems that will inevitably surface as AI gets more widespread adoption? A quick Google search for AI and Cybersecurity will show thousands of pages talking about how AI is revolutionising cybersecurity, but it's extremely hard to find a page which discusses how cybersecurity is helping improve AI and making it safer. Browsing the websites of the top cybersecurity companies will render similar results: no mention of applying cybersecurity research to find vulnerabilities in AI algorithms. This is, however, not surprising at all. AI and Deep Learning is a relatively new discipline and is only starting to take off relatively recently. Moreover, there are still few use cases where it is paramount to guarantee the AI algorithms have no life-threatening vulnerabilities. But as AI takes over more and more tasks such as driving, flying, designing drugs to treat illnesses and so on, AI engineers will need to also learn the craft of, and be, cybersecurity experts. I want to emphasise that the responsibility of engineering safer AI algorithms cannot be delegated to an external cybersecurity firm. Only the engineers and researchers designing the algorithms have the intimate knowledge necessary to deeply understand what and why vulnerabilities exists and how to effectively and safely fix them. External cybersecurity companies may play a role of trying to "pen test" the algorithms, but ultimately it will be up to the engineers developing them to fix them. Naturally this can only happen when AI engineers master the craft of security applied to AI algorithms. If AI is a relatively new field, security applied on AI algorithms is even newer and hiring people with such expertise will be a massive challenge. But inevitably AI engineers will need to take security under consideration and proactively test their algorithms for possible malicious attacks and also become security experts. Companies and their leaders will also need to start to take this topic seriously. No organisation wants to create unsafe products to begin with, and surely no organisation wants to be on the news for how easily their AI systems were fooled or what fatal accident their algorithms caused. So, if you're a company that designs AI algorithms which are applied to critical areas of people's lives: deploy a culture of safety and security inside your AI engineering teams.

The Inevitable Symbiosis of Cybersecurity and AI

A CGI view of the underground network of tree roots and fungi. Screenshot from movie Fantastic Fungi . The pandemic is helping us appreciate the key role of the internet in our lives and a reminder of how much more there is to build on it. A deep and complex underground network runs under our feet. This network provides plants and trees with beneficial nutrients, enables them to communicate with each other through chemical stress-signals, and shields them from external pathogens ( ). New York Times 2016 This is a fungal network, made up of root-like filaments called mycelium. Without this underground network forests would be nutrient-poor, more prone to suffering diseases and each plant siloed from one another. Can you think of any similar network existing in our lives? Well, this network is called the for a reason. It takes its name from the internet for its stark resemblance. Similarly, the internet is a network that enables light-speed and frictionless communication throughout the human ecosystem and provides it resilience against external threats. ‘wood wide web’ John Hopkins COVID-19 global monitoring data has been the world-wide real-time interface for monitoring the status of the virus. As the Corona pandemic quarantined our countries and locked down our societies, the internet is playing a key role in not only tackling the spread of the virus and finding a cure, but in enabling many of us to resume life as usual in these unusual times. This is true be it in matters of work (the lucky ones started remote working), living and play (the internet has become a main source of leisure — try buying a gaming console these days!), or socialising (it has also become our primary communication tool). My hope here is to help us appreciate how the internet is serving us in these challenging times thanks to its boundless potential; and and yet to show how much more the internet has to offer. The big picture of the internet economy (spoiler: it’s still small) Unsurprisingly, the Big Tech players are kings of this space and take the largest slice of the pie: Facebook and Google account for approximately , while Amazon accounts for roughly in the USA. The US internet economy is roughly 10% of its entire GDP, based on a 2019 study . 84% of global digital ads 50% of all online retail spending These figures are usually lower for most other countries, except for rapidly growing emerging countries like China. Granted, calculation methodologies may differ so a like for like comparison between the US and China may not be suitable. But one thing is certain: China’s internet economy represented over 35% of its GDP in 2018 . We are still in the relatively early stage of the internet revolution. A 10% internet economy in the US tells us that there is still a bulk of the economy offline — which would likely benefit from online channels. So how is our society’s response to the coronavirus pandemic leading us deeper down into the internet rabbit hole? Glad you asked: The lockdown pushes people online Steady state internet economy growth represented in black, and the new steady state curve being created by the pandemic-led lockdown in grey. This is a conceptual graph so does not represent real data. As of the 26th of March, over , that is almost 1 in 3 people worldwide, and are forced to either work from home or not work at all. Either way, this is leading to unprecedented levels of internet usage which, as a consequence, is creating all sort of technical issues. Here are some that I came across: 2.8 billion people have been put in lockdown and s are downgrading their streaming quality by around 25% on European networks in March — and the measure is likely to be extended. Netflix other major streaming service following the flooding of the game by quarantined children from around the world. Fortnite gamers are experiencing major outages Microsoft Azure Cloud seems to be . Azure’s corporate clients reliability and capacity issues, which doesn’t seem to be scaling quickly enough to accommodate peaks in demand. “having issues” are reporting These qualitative indicators show us that the lockdown has greatly increased our demand for internet tools and services. We will definitely see a rebound to a back-to-normal way of working and interacting. But this doesn’t mean that all these digital ‘underground’ experiments will have been for nothing. The virtualisation of our work and social lives will endure as our society grasps the added benefits and value of online tools, and as new tools fit for purpose are built to optimise our experiences. Let’s look at some of the new tools that have sprung up during the pandemic: Virtual events and conferences As pre-planned events and social gatherings are increasingly being postponed, cancelled, or going ‘virtual’, online conferencing tools are in high demand. Here are some of the tools I came across in the last month that people are using during the pandemic: , see picture above, is a new conferencing tool that enables people to ‘see’ themselves in 2D virtual spaces, while also video-conferencing. It enables people’s 2D avatar to sit in virtual tables alongside other attendees, while listening to the speakers, whose avatars take the stage. Remo.co is also growing in usage, providing event builders and broadcasters the platform to post their events to specific guests or the general public, and to request payments directly on the platform. Once users join the event, only the hosts appear on video and users can provide feedback and comment through a communal chat. CrowdCast Both tools provide the ability for people globally to take part in these events. Noteworthy is how Remo tries to create virtual places and selves as 2D avatars. And while this feature certainly helps to ‘imagine’ our place in a conference hall, it is still far away from creating the feeling of ‘being’ there. Social distancing & video conferencing Whether one might use it for catching up with groups of friends or doing work calls with colleagues (that doesn’t involve being subject to the many Skype glitches) social video conferencing has seen at least two big winners during the pandemic. , as you’ve probably noticed, has become the de facto group communication tool during the Coronavirus lockdown. To the extent that it features as being the ‘culprit’ of the virus in a number of memes. It makes it much easier to invite people on conference calls, provides a seamless video conferencing for up to 300 users, free video conferencing for calls up to 40 min. long, and, some would suggest, fun backgrounds. Zoom is another social media phoenix emerging out of the pandemic’s ashes. It is a quirky app, designed for younger audiences, that enables users to form social circles, move in and out between them, and interact with others by playing games, make drawings, and more. It has definitely managed to carve its own unique place between social media (like Facebook) and video comms tools (like Skype or WhatsApp). HouseParty These social platforms are easy to use and provide us the instant ability to connect with those we normally interact with in our daily life, be it colleagues, friends and family. They also are beginning to provide a level of interactivity through in-built games. Benefits provided by these platform experiences Be it in events, socialisation or work, online tools have a lot to offer: It takes the click of a mouse (or the downloading of an app) to instantly connect with others. Making communication super easy and quick: People sharing similar interests can now join global conferences from their living rooms. To be participative and engaged, it no longer matters where in the world you’re located. Shrinking geographies: Online platforms are highly elastic and mouldable to be fit for purpose. Think it’s creepy how HouseParty allows users to spy on who their friends are talking to? (Me too). But this feature was designed in an effort to make their younger users interested in joining their friends’ parties (and, who knows, maybe also to allow their parents to keep an eye on the party from outside its virtual door). The point being: it’s easy to plug in and repurpose features to these apps so they better serve us as our way of using them evolved. Thank the APIs! Expanding features and possibilities: Although there is a need for growth here (as we’ve seen communication tools are mostly video-based which are fixed and offer a limited interaction potential), the online solutions we looked at are beginning to display in-app interactivity through integration of games, drawing boards and creative background. This creates the possibility for richer social dynamics more fit for purpose. Increasing interaction through intuitive interfaces: Limitations of these platforms Here are some of the main limitations of the tools I looked at: While video conferencing tools provide a person to person view, we have seen scenarios like events and conferences where users might expect to ‘feel in place’. Perhaps this is something that Virtual Reality (VR) can help with. Tools like VRChat, Altspace, Decentraland, and Hubs are proving successful in their own right, so it’s a matter of applying them to the right use cases — be they virtual conferences or workplace roundtables. Interestingly, virtual places don’t necessarily have to represent real places, nor do you necessarily need a human avatar of yourself — places and selves may be as realistic as the purpose of your interaction requires. Lack of a feeling of virtual place: Example: if you are having a meeting with colleagues all that needs to be transferred is your voice, and the image of your mouth and eyes (which help to decode the voice), but beyond that it’s all up for grabs! You might as well give the option to do a videoconference as a potato (see above). In Remo.co we saw the possibility of moving one’s 2D icon around the virtual conference, and in Houseparty one can play games and make drawings while on the call. I am sure we all agree that so much more can be done here. Material objects in the real world are really important, they help us to ground our experiences and make more meaning out of them. E More interaction with virtual objects: xample: in  the face-to-face meetings I have with my colleagues we often use the whiteboard to write down ideas and represent our thoughts visually. Now, virtual objects fit for purpose could enable many possibilities and greater experiences in specific realms of our work and social lives. The early vision of the internet J.C.R. Licklider. In the article titled visionary and pioneer of the computer and the internet, by the name of J.C.R. Licklider, said: The Computer as a Communications Device (1968) , a “In a few years, men will be able to communicate more effectively through a machine than face to face. That is a rather startling thing to say, but it is our conclusion”. These were the 1960’s, and we can safely say that Licklider had it right already back then (let us forget for a minute those glitchy Skype calls!). While the internet has revealed plenty of its flaws in the last few years — from rampant fake news and nonexistent data privacy — we often forget to look at the big picture view of how crucial the internet and the entire computing revolution have been to advance humanity. Now, I’d say that the COVID-19 crisis reminded us of the big picture view. In the midst of this pandemic, the internet connected people with similar interests to meet in virtual conference rooms despite their geographical distance, enabled workers to carry out their tasks remotely, brought friends and family together despite a physical lockdown, gave us the ability to monitor the spread of the virus real-time and forecast its effects in our communities, allowed scientists from all nations to collaborate in search for a vaccine, and much much more. If there is at all a tech-related silver lining to this pandemic crisis, it must be the collective realisation that society and much of the economy can still function during a global lockdown thanks to the internet. The human-internet symbiosis Another  CGI view of the underground network of tree roots and fungi. Screenshot from . Fantastic Fungi J.C.R. Licklider saw our relationship with computers as symbiotic. He believed that this was a profitable relationship for humans. Computers, he said, would ( ). And here too Licklider had it right. “augment the human intellect by freeing us from mundane tasks” Man-Computer Symbiosis, 1960 We might even say that the internet reaches beyond Licklider's vision. The internet and digital technologies have the ability to free us from our physical limitations: we can re-create what is possible in physical reality and design new scenarios that transcend what is possible in the real world. Remembering the , trees are unable to communicate with each other with their leaves but they are able to do so ( !) through their alliance with fungi. And this symbiosis makes them stronger as a species: as they are able to prepare and prevent against the threat of all sorts of enemies, be they above or below ground. wood wide web with up to 40 trees surrounding them Similarly to the symbiosis between trees and fungi, our symbiosis with the internet enables us to come together as humanity to fight external threats. Perhaps, when building the internet and the online services of the future, nature might continue to be a source of inspiration for us. The Uncensored Library in Minecraft houses a massive protected library in which anyone can come and visit censored stories from around the world. I find this to be a powerful symbol of the places we can build and inhabit on the internet (Bleeding Cool).

The Pandemic is Deepening our Symbiosis with the Internet

Photo by John Schnobrich on Unsplash Gambling is one of the oldest recreational activities in the history of mankind. Its most ancient records date all the way back to the Paleolithic period. The earliest six-sided dice, the one we know today, has been traced back to Mesopotamia some 5,000 years ago! It’s how many Roman soldiers liked to pass their time, wagering their hard-earned coins against each other for fun, and for the chance to end the day with a heavier coin purse. Blockchain casinos are set to be the latest iteration of the online gambling and sports betting industry. Shift back to modern day and we see that . Multiple new game forms have entered the fray and a whole gigantic industry has been built around iconic games like the roulette, poker, sports betting and many others. The Internet helped escalate this to an entire new level with companies being able to offer players the chance to gamble on anything they like from the comfort of their own home. The ubiquitous use of mobile devices further contributed to this growth. gambling has evolved in uncountable ways It is a well documented fact that our DNA has been almost hard-coded to enjoy the thrill of putting our stake on an event whose outcome we don’t know. The variations in levels of neurochemicals such as dopamine are the main drive behind the addictive aspect of gambling. . It comes as no surprise that the entire online gambling market was evaluated at $44 billion in 2016 and is estimated to reach $80 billion by 2022 The global casino market gross gaming yield helps visualize this trend: Retrieved from Statista Keep in mind that none of these numbers take into account all the unthinkable sums of money that are wagered on worldwide. It’s understandably hard to pin down a solid number but vary from to dollars. illegal gambling estimates $80 $380 billion The industry has definitely come a long way and cemented itself into the world of business. However the modern industry practices are from perfect. . From a technological viewpoint the internet is a marvel and it did a wonderful job proliferating industries like this to people all around the globe. However as things stand today it lacks the tools required to overcome the hurdles that plague online casinos and sports books. What are these hurdles? far It has major downfalls that affect the gambling houses, regulators and of course most importantly, the players Lack of transparency and fairness By Masaaki Komori on Unsplash The notable lack of transparency and fairness is something that has afflicted gambling and betting enthusiasts for a long time. . This isn’t always the case, and there is hardly anyway to check if the casino software algorithms are legit or not. If a player is particularly skilled in what he’s doing than he’s even more prone to see his or her winnings cut short by the house. Players have no choice other than to trust the online platforms that they are not being cheated Sports betting platforms are infamous for having everything built around luring the players into losing money, maximizing potential profits in favor of the house. Brick and mortar casinos have notoriously received for cases when members of the security team abruptly approach winning players and put an end to their streak for no particular reason and with no proof of foul play. bad press In online casinos this can be done in a much more silent and subtle way and players won’t even notice. Although most players don’t experience any issues with online gambling houses, there have been numerous cases of complaints regarding payments and bonuses that weren’t properly carried out. Askgamblers alone to have helped over . claims 7,000 players retrieve over $16M in what would be otherwise lost funds Regulation issues High-end regulators often struggle to keep up with the pace of changes to the online gambling industry. And thanks to the bad press around it, the increasing regulatory pressure is not taken slightly by them. Furthermore if the regulations in one country or jurisdiction do not please the company behind online casinos and sportsbooks, it is not unlikely that it will pack up its things and “move” to an offshore regulatory heaven. Securing licenses in places like Curaçao is an industry standard to keep regulatory issues away while also avoiding taxes. This invites users to play in such platforms in hopes of getting better terms, like odds in sports betting events. Often players do this illegally, sometimes without knowledge of the illegality of their actions. The result is not only a tax problem for the country in which those players reside, but also a problem for the players themselves. In a case of rightful complaint they have no legal way to defend themselves. High Entry Barrier To open up account on online platforms players are forced to give up their sensitive personal data like name, address and credit card number. . Deposits and payouts are not instant, and again, lack of transparency, fairness and efficient regulations discourages players from joining. between online gambling houses and potential new players, sapping the industry of the power to reach its full potential. It is far from anonymous This creates friction Blockchain to the rescue? Scott Rodgerson on Unsplash In short, is the revolutionary behind famous cryptocurrencies like and . It is like a decentralized ledger database that operates transparently in a distributed network of computers. It is also capable of running programs that execute under, and only under certain conditions or rules a.k.a s . It’s quite more complex than this, but think of Bitcoin and Ethereum as a fancy programmable form of money, and of blockchain as the database of all the transactions done with these currencies. blockchain Bitcoin Ethereum mart contracts Thanks to this, smart contracts transactions can happen automatically and almost , without the need of going through a third party or central server database. . instantaneously The conditions and rules that apply to these contracts are also enforced automatically by the code that underpins them Whether people like cryptocurrencies or not, the blockchain has come to stay and help improve our lives in ways that we don’t even know yet. It’s compared to the birth of the Internet in the early nineties. What solutions does this bring? If you’ve been in this space for long enough you know how blockchain and its associated cryptocurrencies are changing many of the industries we know today, and even opening doors for new ones and new business models. The relationship between this technology and online gambling however, is one that instantly and vigorously stands out. Remember what the Internet did to mail and messaging back in the day…? So let’s start with the lack of transparency and fairness we mentioned earlier. Blockchain can improve this in more than one way. It can setup the possibility of players to play directly against each other, . Remember, the blockchain is decentralized, there is no need to go through the casino servers in order to wager against a player or a group of players. All payouts can then be carried out by the smart contract protocols we mentioned. It gives the house absolutely no chance to tamper with these payouts, including bonuses and promotions. in a true peer-to-peer system This peer-to-peer gambling creates the chance to bring back the good old days of (technically called ), which the online industry has failed to replicate so far thanks to the lack of technology that would allow it. This is an example of online gambling houses being able to offer players new kinds of services. This concept is already used in some blockchain sportsbooks like . mutual betting Pari-mutuel betting OneHash Provably fair . It means that the casinos can . This is only truly possible through blockchain technology. Since the birth of this concept, the demand for provably fair games has been steadily growing. Gambling houses can offer the players the chance to see the open-source code of the games, or offer other tools for the players to check that they are not being cheated. This is understandably one of the big guns that blockchain casinos have to show for themselves prove that the games they offer are fair and abide by the rules of the game itself Google searches for “Provably fair” over the last 10 years. Viewed on Google Trends This is also beneficial for the casinos because it removes the need for another third party to audit their software. Should the need for a third party verification arise though, the process would be remarkably simpler, which leads us to our next topic. Regulation benefits Regulating blockchain technologies and cryptocurrencies is still a hotly debated topic. However , as well as applicants or licensees. It provides a safe environment for storing and tracking information about transactions, while allowing reliable third-party verification. One could almost be led to think that in the future, regulators would be tempted to require online gambling houses to operate with this technology in order to make their lives easier. many fundamentals aspects this technology may in fact come to the rescue of regulators Take money laundering as an example. The possibility to audit the blockchain in order to review transactions across different operators, and then compare accounts that might be using them to place bets in both sides of events in order to launder dirty money would be a game changer. When it comes to pre-licensing investigations and suitability checks, blockchain-based technology can also help relief concerns regarding standardization and data protection. Lower entry barrier This is very beneficial for online casinos, as we already see happening today. Whether it is just a regular online casino that accepts Bitcoin (or other cryptos) like , or entirely blockchain-based casinos, the process of getting started is much simpler and faster. . The deposit is then quickly processed, sometimes even instantly depending on the cryptocurrency used. In other cases, all you need is the MetaMask browser extension. 1xBit No personal data is required, just an e-mail, a wallet address and a password Being able to bet and gamble without the need of disclosing sensitive data stimulates business. Players can get started within minutes, sometimes even testing out the games for free with whatever amount they can get from the platform’s faucet. Privacy concerned customers who don’t want any gambling bills showing up in credit card statements won’t need to look any further. Security Just this year came out of a casino that had its high-rolling customer database hacked through a thermometer in the lobby fish tank (pretty amazing!). With hackers getting more and more sophisticated, cyber security startups are making a killing as more companies want to be sure that their data is fully secure. Because the blockchain is decentralized, hackers have no central server to attack in order to steal or corrupt data. Bitcoin’s blockchain has been running with 100% uptime and no successful hacks ever since its inception in 2009. news Disruption Potential There is still no way to tell if blockchain technologies will be the future industry norm for online gambling. . However the many intricacies that assemble the blockchain technology will bring new building blocks to this industry Players, regulators and the gambling houses themselves have multiple reasons to welcome it. It is that the online gambling market will reach by 2022. This is the number that blockchain casinos startups will be hoping to tap int. However keep in ming that the global casino market value is much higher at Some casinos have already started to accept cryptocurrency payments, but . In these cases the offer is restricted to deposits and payouts being conducted with Bitcoin or its siblings, which offers some advantages. estimated $80 billion $500 billion. this has nothing to do with being blockchain-based In order to reap all the benefits we mention in this article, a casino would need to run entirely on a blockchain’s decentralized network. Many ICO’s of this kind resort to creating their own token within Ethereum’s chain. Ethereum still operates with some limitations on number of transactions per second, but the resources being poured into improving this are tremendous. FunFair FunFair’s idea is to create games that can only be played using their FUN token (ERC20). What’s impressive about FunFair is how they want to tackle regulation in order to make their product work. They are in talks with many regulators from countries like Malta, which has proclaimed its open policy toward blockchain businesses. They have even for a license in the UK. Other operators would then be able to incorporate their games in their own platforms using FunFair’s license. Like a form of . applied license white labeling Edgeless Edgeless is also an ERC20 token. The difference here is that Edgeless have a fully functional that offers players the ability to play dice and blackjack using their EDG token. They have laid out plans to futurely include poker and sports betting. platform TrueFlip TrueFlip offers their players lottery games that can be played with many cryptocurrencies. Once again you can expect their lottery fairness to be fully auditable, even by yourself. Their ERC20 token TFL offers extra to its holders. rewards Lottery draws happen all the time and in order to participate users have to buy a ticket. They currently offer 4 original games. Conclusion Symbiosis: a mutually beneficial relationship between different people or groups Many new projects are looking to take advantage of blockchain technology to implement it on the online gambling and sports betting business. The advantages are plenty and clear to see. With good implementation the impact on the industry would be huge. Financially speaking, if we judge by market cap only, the biggest of the three we mentioned here is FunFair. Their market cap at the time of writing is $100M. Edgeless sits at $27M. The two combined ($127M) are only a tiny minuscule fraction of the market value of the whole industry. If by estimate the whole blockchain casino industry can grab 10% of the online gambling market, they would sit at a market value of . a conservative $8 billion From a qualitative perspective the cards have all been dealt for blockchain casinos and sports betting platform to lead an inevitable industry improvement. Things are just getting started. Originally published at https://casinosblockchain.io on July 13, 2018.

Blockchain and Online Casinos: Technological Symbiosis

Blockchain And Gold: A Fruitful Symbiosis

Symbiosis Instead of Dichotomy: PoW and PoS-mining

This paper is under CC 4.0 license. available on arxiv Authors: (1) Zhe Liu, State Key Laboratory of Intelligent Game, Beijing, China Institute of Software Chinese Academy of Sciences, Beijing, China; University of Chinese Academy of Sciences, Beijing, China; (2) Chunyang Chen, Monash University, Melbourne, Australia; (3) Junjie Wang, State Key Laboratory of Intelligent Game, Beijing, China Institute of Software Chinese Academy of Sciences, Beijing, China; University of Chinese Academy of Sciences, Beijing, China & Corresponding author; (4) Mengzhuo Chen, State Key Laboratory of Intelligent Game, Beijing, China Institute of Software Chinese Academy of Sciences, Beijing, China; University of Chinese Academy of Sciences, Beijing, China; (5) Boyu Wu, State Key Laboratory of Intelligent Game, Beijing, China Institute of Software Chinese Academy of Sciences, Beijing, China; University of Chinese Academy of Sciences, Beijing, China; (6) Zhilin Tian, State Key Laboratory of Intelligent Game, Beijing, China Institute of Software Chinese Academy of Sciences, Beijing, China; University of Chinese Academy of Sciences, Beijing, China; (7) Yuekai Huang, State Key Laboratory of Intelligent Game, Beijing, China Institute of Software Chinese Academy of Sciences, Beijing, China; University of Chinese Academy of Sciences, Beijing, China; (8) Jun Hu, State Key Laboratory of Intelligent Game, Beijing, China Institute of Software Chinese Academy of Sciences, Beijing, China; University of Chinese Academy of Sciences, Beijing, China; (9) Qing Wang, State Key Laboratory of Intelligent Game, Beijing, China Institute of Software Chinese Academy of Sciences, Beijing, China; University of Chinese Academy of Sciences, Beijing, China & Corresponding author. Table of Links Abstract and Introduction Motivational Study and Background Approach Experiment Design Results and Analysis Discussion and Threats to Validity Related Work Conclusion and References 8 CONCLUSION Automated testing is crucial for helping improve app quality. Despite the dozens of mobile app GUI testing techniques, how to automatically generate the diversified unusual text inputs for fully testing mobile apps remains a challenge. This paper proposes InputBlaster which leverages the LLM to produce the unusual inputs together with the mutation rules which serve as the reasoning chains. It formulates the unusual inputs generation problem as a task of producing a set of test generators, each of which can yield a batch of unusual text inputs under the same mutation rule. The evaluation is conducted for both effectiveness and usefulness, with 136% higher bug detection rate than the best baselines, and uncovering 37 new crashes. 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Leveraging LLMs for Generation of Unusual Text Inputs in Mobile App Tests: Conclusion and References

The infusion of digital assets into sports is not just a fleeting trend but a profound disruption. It is reshaping everything from fan engagement to financial transactions, sponsorship deals, and even the very essence of sports memorabilia. Let's dive into how cryptocurrency is revolutionizing the sports realm. Fan Engagement and Experiences Cryptocurrencies are redefining the way fans interact with their favorite sports and teams. The introduction of fan tokens, for example, allows supporters to vote on minor club decisions, access exclusive content, and even engage in unique experiences. Consider the scenario where a prominent football club sold out its fan tokens in less than 20 minutes, generating over $1.3 million in revenue. Such initiatives enhance the fan experience, fostering a deeper sense of involvement and loyalty. In the digital age, the sports industry is witnessing a revolutionary shift in fan engagement and experiences fueled by the integration of cutting-edge technologies. Cryptocurrencies and blockchain are at the forefront of this transformation, enabling interactive and immersive experiences that deepen fan loyalty and participation. Through the creation of fan tokens, supporters are not just spectators but active participants, influencing club decisions, accessing exclusive content, and enjoying unique game-day experiences. These digital assets offer fans a new level of involvement, transcending traditional boundaries and fostering a deeper connection with their favorite teams and athletes. As this trend gains momentum, it's clear that the future of fan engagement is not just about watching the game but being an integral part of the sports narrative. The result? A more dynamic, interactive, and enriched fan experience that's setting new standards in the world of sports. Transforming Sports Sponsorships and Partnerships In the realm of sponsorships, cryptocurrencies are making a notable mark. Major sports teams and leagues are entering into lucrative partnerships with crypto platforms, illustrating the industry's growing acceptance of digital currencies. For instance, a leading crypto exchange recently signed a $135 million naming rights deal with a renowned sports arena. These collaborations not only provide substantial financial backing but also integrate cryptocurrency into the mainstream sports narrative. A spotlight on the Thunderpick World Championship underscores the symbiosis between sports and crypto and has acted as a case study for crypto’s sports impact. This esports tournament not only features a significant crypto-based prize pool but also integrates blockchain technology for transparent and secure processes. Such events exemplify how cryptocurrency is not just an ancillary element but a core feature that enhances the competitiveness and global reach of sports events. Facilitating Global Transactions and Expanding Reach Cryptocurrency's borderless nature is a boon for international sports transactions, enabling seamless, secure, and swift payments across the globe. This is particularly beneficial for international sports leagues and athletes, eliminating the hurdles of currency conversion and transfer delays. The ease of crypto transactions is instrumental in the rapid globalization of sports, allowing teams, leagues, and athletes to engage with a broader, more diverse audience. In today's digital age, cryptocurrency is not just a financial trend but a pivotal tool in bridging the gap between global markets and industries. Its borderless nature facilitates seamless international transactions, eliminating traditional banking barriers and currency conversion hassles. For businesses, this means an expansive reach into new markets, fostering cross-border partnerships with unprecedented ease. Cryptocurrency's decentralized framework ensures secure, transparent, and swift transactions, providing a robust foundation for global commerce. This digital revolution is particularly transformative for industries like e-commerce, tech, and digital services, where the ability to operate and transact globally is synonymous with growth and innovation. Embracing cryptocurrency is not just about adopting a new form of currency; it's about unlocking a world of opportunities, fostering global connections, and paving the way for a truly interconnected market landscape. Revolutionizing Sports Memorabilia with NFTs Non-fungible tokens (NFTs) are a groundbreaking aspect of crypto's integration into sports, revolutionizing the concept of memorabilia. Digital collectibles, authenticated and secured via blockchain, offer fans unique, tamper-proof ownership of sports moments, art, and more. The sale of an iconic sports moment as an NFT, for instance, fetched over $2 million, illustrating the potent combination of sports nostalgia and cutting-edge technology. Conclusion: Embracing a New Era in Sports The integration of cryptocurrency into the sports industry is not merely a trend but a profound evolution that's reshaping how we perceive and interact with sports. From enhancing fan engagement to revolutionizing memorabilia, crypto is laying the groundwork for a more interactive, secure, and globally connected sports ecosystem. As we witness innovations like the Thunderpick World Championship, it's clear that the fusion of sports and crypto is not just the future—it's the present. The sports world is in the midst of a digital renaissance, and embracing this change is pivotal for its growth, sustainability, and relevance in the digital age. The infusion of digital assets into sports is not just a fleeting trend but a profound disruption. It is reshaping everything from fan engagement to financial transactions, sponsorship deals, and even the very essence of sports memorabilia. Let's dive into how cryptocurrency is revolutionizing the sports realm. Fan Engagement and Experiences Cryptocurrencies are redefining the way fans interact with their favorite sports and teams. The introduction of fan tokens, for example, allows supporters to vote on minor club decisions, access exclusive content, and even engage in unique experiences. Consider the scenario where a prominent football club sold out its fan tokens in less than 20 minutes, generating over $1.3 million in revenue . Such initiatives enhance the fan experience, fostering a deeper sense of involvement and loyalty. $1.3 million in revenue $1.3 million in revenue In the digital age, the sports industry is witnessing a revolutionary shift in fan engagement and experiences fueled by the integration of cutting-edge technologies. Cryptocurrencies and blockchain are at the forefront of this transformation, enabling interactive and immersive experiences that deepen fan loyalty and participation. Through the creation of fan tokens, supporters are not just spectators but active participants, influencing club decisions, accessing exclusive content, and enjoying unique game-day experiences. These digital assets offer fans a new level of involvement, transcending traditional boundaries and fostering a deeper connection with their favorite teams and athletes. As this trend gains momentum, it's clear that the future of fan engagement is not just about watching the game but being an integral part of the sports narrative. The result? A more dynamic, interactive, and enriched fan experience that's setting new standards in the world of sports. Transforming Sports Sponsorships and Partnerships In the realm of sponsorships, cryptocurrencies are making a notable mark. Major sports teams and leagues are entering into lucrative partnerships with crypto platforms, illustrating the industry's growing acceptance of digital currencies. For instance, a leading crypto exchange recently signed a $135 million naming rights deal with a renowned sports arena. These collaborations not only provide substantial financial backing but also integrate cryptocurrency into the mainstream sports narrative. $135 million naming rights deal $135 million naming rights deal A spotlight on the Thunderpick World Championship underscores the symbiosis between sports and crypto and has acted as a case study for crypto’s sports impact. This esports tournament not only features a significant crypto-based prize pool but also integrates blockchain technology for transparent and secure processes. Such events exemplify how cryptocurrency is not just an ancillary element but a core feature that enhances the competitiveness and global reach of sports events. Thunderpick World Championship Thunderpick World Championship Facilitating Global Transactions and Expanding Reach Cryptocurrency's borderless nature is a boon for international sports transactions, enabling seamless, secure, and swift payments across the globe. This is particularly beneficial for international sports leagues and athletes, eliminating the hurdles of currency conversion and transfer delays. The ease of crypto transactions is instrumental in the rapid globalization of sports, allowing teams, leagues, and athletes to engage with a broader, more diverse audience. In today's digital age, cryptocurrency is not just a financial trend but a pivotal tool in bridging the gap between global markets and industries. Its borderless nature facilitates seamless international transactions, eliminating traditional banking barriers and currency conversion hassles. For businesses, this means an expansive reach into new markets, fostering cross-border partnerships with unprecedented ease. Cryptocurrency's decentralized framework ensures secure, transparent, and swift transactions, providing a robust foundation for global commerce. This digital revolution is particularly transformative for industries like e-commerce, tech, and digital services, where the ability to operate and transact globally is synonymous with growth and innovation. Embracing cryptocurrency is not just about adopting a new form of currency; it's about unlocking a world of opportunities, fostering global connections, and paving the way for a truly interconnected market landscape. The ease of crypto transactions The ease of crypto transactions Revolutionizing Sports Memorabilia with NFTs Non-fungible tokens (NFTs) are a groundbreaking aspect of crypto's integration into sports, revolutionizing the concept of memorabilia. Digital collectibles, authenticated and secured via blockchain, offer fans unique, tamper-proof ownership of sports moments, art, and more. The sale of an iconic sports moment as an NFT, for instance, fetched over $2 million, illustrating the potent combination of sports nostalgia and cutting-edge technology. Non-fungible tokens (NFTs) Non-fungible tokens (NFTs) Conclusion: Embracing a New Era in Sports The integration of cryptocurrency into the sports industry is not merely a trend but a profound evolution that's reshaping how we perceive and interact with sports. From enhancing fan engagement to revolutionizing memorabilia, crypto is laying the groundwork for a more interactive, secure, and globally connected sports ecosystem. As we witness innovations like the Thunderpick World Championship, it's clear that the fusion of sports and crypto is not just the future—it's the present. The sports world is in the midst of a digital renaissance, and embracing this change is pivotal for its growth, sustainability, and relevance in the digital age.

Blockchain is Shaping the Future of Athletics

As an AI expert, let me be blunt - cyber threats are a massive, unrelenting risk that no business with an online presence can afford to ignore these days. Whether you're running an e-commerce site, logistics operation, or tech firm, phishing, ransomware attacks, or data breaches - these scourges can cripple a company, leading to devastating financial losses, irreparable brand damage, and even regulatory penalties that could bury you. I've personally seen the aftermath of cyber strikes on SMBs with limited security resources and tight budgets. In those cases, traditional cybersecurity just doesn't cut it against today's attack of threats. But that's exactly where artificial intelligence (AI) emerges as a total game-changer. discovered that organizations leveraging AI and automation extensively saved a mind-blowing $1.76 million on average compared to their less AI-savvy counterparts. IBM's 2023 Cost of Data Breach Report And I can testify that AI-powered cyber defense solutions truly earn those savings. By unleashing cutting-edge AI techniques like machine learning, deep learning models, and natural language processing, modern AI cybersecurity acts like an indispensable digital force multiplier reinforcing our defenses against even the wiliest adversaries. As an AI expert, I've deployed these capabilities for clients - it's like having an entire squad of cybersecurity sentries patrolling the digital premises 24/7 to keep the bad actors at bay. Moving forward, I don't believe adopting advanced AI will be a luxury for organizations - it's a flat-out necessity we can't ignore. Whether you're a small business or a giant enterprise, you'd better get proactive and start leveraging AI's offensive cybersecurity potential to safeguard your vital digital assets and ensure continuous operations. In my opinion, AI is quickly separating the cybersecurity haves from the have-nots. AI's Cyber Offense: How It Turbocharges Threat Detection I can't overstate how AI is revolutionizing cybersecurity by unleashing cutting-edge threat detection and response capabilities never before possible. Just look at the rapidly growing market - projects that AI in the cybersecurity sector will explode from $22.4 billion in 2023 to $60.6 billion by 2028. And there are good reasons behind that meteoric growth. MarketsandMarkets Machine learning algorithms excel at quickly identifying patterns and anomalies within massive datasets - making them invaluable assets for recognizing potential cyber threats amid tons of network traffic, user activity logs, and other data. By training these algorithms on historical data, we can have them recognize known attack signatures and deviations signaling new threats before they can wreak havoc. One study I find particularly compelling is from MDPI, showing machine learning models achieved up to 99% malware detection accuracy using techniques like Decision Trees, Convolutional Neural Networks, and Support Vector Machines. That's the level of precision AI can deliver against emerging threats. There are deep learning models that I've deployed to rapidly analyze and classify malware samples with incredible accuracy. The latest deep-learning architectures can see patterns invisible to the naked eye. However, some of the most exciting AI cybersecurity applications my team has tested involve reinforcement learning for adaptive threat response. These self-learning systems can dynamically adjust defensive actions on the fly based on their experiences against evolving attack vectors. Allied Market Research predicts reinforcement learning will see explosive 41.5% annual growth from 2023 to 2032, with cybersecurity as a prime use case. Let's not overlook natural language processing (NLP) for automating incident analysis. I've personally overseen NLP deployments that can rapidly comprehend human language data from reports, intelligence feeds, and more - streamlining our incident response workflows and prioritizing genuine threats over false positives. Combining all these AI disciplines is delivering incredible offensive capabilities to counter even the trickiest cyber adversaries. As an expert and founder in this space, I truly believe AI's ability to autonomously detect and shut down threats before impact will utterly transform cybersecurity over the coming years. Why UEBA and User Behavior Monitoring Matter (And How AI Excels) The cyber risk from malicious insiders or compromised user accounts is one we can't overlook either. That's why I consider user and entity behavior analytics (UEBA) powered by advanced AI/ML models to be paramount for comprehensive, 360-degree security visibility. At a basic level, these AI-driven UEBA solutions leverage machine learning to establish baselines modeling each user's normal behavior based on their activity patterns. Once those baselines are established, the AI can continuously monitor for deviations that may indicate insider threats, privilege abuse, compromised accounts, and other insider risk vectors. What makes this application of AI so powerful is its ability to dynamically score the risk level of unusual user actions based on contextual factors like their role, access privileges, the sensitivity of data/systems involved, and more. This enables real-time flagging of potentially malicious insider activity for further investigation - something that was highly prone to human error with traditional, rigid rule-based approaches. Another area where I've seen UEBA with AI shine is detecting compromised privileged user accounts, which are prime targets for external threat actors seeking a foothold. By understanding the unique behavior patterns of different privileged user roles, AI can rapidly identify the subtle anomalies of a privileged account under hostile control - giving our teams a chance to shut down that breach before catastrophic damage occurs. In my opinion, deploying AI for insider and privileged user threat detection by understanding human behavior is an absolute game-changer. Monitoring our people and accounts is just as vital as external threat monitoring - without it, we're leaving a gaping hole in our defenses that skilled adversaries will inevitably find and exploit. Of course, my teams always emphasize that AI-powered UEBA is just one layer in a comprehensive, defense-in-depth strategy. But it's a crucial layer that lets us get in front of insider incidents before they escalate - buying time that can mean the difference between a contained issue and a full-blown crisis. The Flip Side: Defending Against AI-Powered Threats As amazing as AI's cybersecurity offensive capabilities are, I have to address the flip side too: hackers are actively working on ways to weaponize AI against us. Adversarial attacks designed to bypass, poison, or steal our AI models are a clear and present danger we can't ignore. One disturbing forecast from research analysts indicates: Up to 30% of AI cyberattacks will leverage training data poisoning, model stealing, or adversarial examples to attack AI-powered systems. But we're not defenseless - there are proven ways to harden AI systems against these tactics if we invest in robust AI security controls from the start. Approaches like adversarial training, where models are intentionally exposed to deceptive inputs during the learning process, can improve resilience against evasion. Differential privacy techniques can also obscure model behavior to thwart extraction attacks. We follow best practices around secure AI development Life Cycle, subjecting our models to rigorous adversarial testing and employing defensive AI techniques to stay ahead of emerging threats. I don't mean to sound alarmist, but the cybersecurity industry at large needs to prioritize battling AI-powered threats just as much as leveraging AI for defense. It's a two-way street - we must secure the AI models underpinning our cyber defenses with the same vigor we apply AI offensively. Neglecting AI security WILL be exploited by sophisticated hackers. So while I'm incredibly confident about AI's potential to revolutionize cyber threat detection and response, I'm also pragmatic. We simply can't ignore the dark side and must proactively invest in developing and deploying AI securely to maintain a decisive strategic advantage. Integrating AI Across Security Operations Of course, AI alone is not a silver bullet for cybersecurity. Its true power comes from thoughtful integration across existing processes, teams, and technology stacks. As an enthusiastic AI Expert, I emphasize this force-multiplier effect to clients constantly. AI should augment and empower human expertise, not replace it entirely. That's why the most successful deployments I've seen use AI to offload tedious, repetitive tasks to machines - freeing up skilled personnel to focus on higher-level analysis, investigation, and decision-making that requires human judgment. That's also why AI is rapidly becoming essential for SOC analysts and incident response teams: by automating alert triage, log analysis and basic response workflows, AI drastically reduces burnout from low-value "grunt work" while improving overall efficiency. Research from Capgemini revealed organizations using AI for security operations saw a 12% increase in breach detection rates and an impressive 19% reduction in time-to-respond. Those are major gains I've validated through my own startup's AI deployments. AI and machine learning are also driving huge advances in security orchestration, automation, and response (SOAR) tools that streamline entire incident response processes. With SOAR, AI handles tasks like correlating disparate security signals, surfacing relevant threat intelligence, and even executing semi-automated response playbooks. It's a huge step towards smarter, more autonomous incident handling. Ultimately though, AI is a complement to skilled human teams, not a wholesale replacement. Cybersecurity operations will always require human expertise, analysis, and judgment. But by intelligently augmenting our people with AI automation and assistance, we can concentrate their talents on higher-impact duties while optimizing productivity and efficiency. I already see this human-machine symbiosis enhancing the industry's ability to outpace threats. As AI integration continues maturing, I'm confident embracing this collaborative model is the only way we'll realistically close the cybersecurity skills gap plaguing our field. AI's Cybersecurity Superpowers By rapidly analyzing network data, user activities, system logs, and more, AI can identify malicious behavior patterns and potential threats with superhuman speed - giving us an early warning to shut down attacks before escalation. Threat Detection & Prevention: While phishing lures and malware grow more devious, AI algorithms can precisely distinguish malicious files and emails from legitimate ones by evaluating content, sender metadata, behavioral signals, and other artifacts that often evade human analysis. Phishing and Malware Detection: Rather than rigid rules, AI lets us dynamically model normal user activity baselines. It can then rapidly detect anomalies indicative of insider threats, compromised accounts, data exfiltration attempts, and more - all in real-time. User Behavior Analytics: I've deployed AI to prioritize vulnerabilities based on their risk and exploit potential, automating the triaging process. AI can also correlate vulnerabilities with active threats, showing us which exposures need patching first. Automated Vulnerability Management: Modern AI-powered SIEM solutions can correlate security events across networks, endpoints, and other sources to rapidly identify genuine incidents amidst the noise. AI also streamlines response workflows based on alert contexts. Smart SIEM & Incident Response: Across incident triage, alert analysis, threat hunting, and more, AI is automating repetitive, labor-intensive security tasks - amplifying the impact of human personnel while reducing burnout and fatigue. Security Ops Automation: I could go on, but you get the idea. As an AI expert and entrepreneur, I've seen these capabilities utterly transform cybersecurity operations into an amazingly proactive, autonomous counter-threat force. And AI's offensive cyber capabilities are still rapidly evolving. The Way Forward: Practical AI Cyber Defense But when I gaze into the future of AI-powered cybersecurity, I see incredible potential beyond just better threat detection and response. Used wisely, I believe AI can fundamentally reshape and elevate our entire profession into a truly proactive, predictive security posture - finally outpacing even the wiliest cyber adversaries. However, realizing this AI-driven future won't happen automatically. It requires us as an industry to thoughtfully and securely integrate AI across our people, processes, and technology stacks with a keen focus on augmenting human expertise and capabilities rather than wholesale automation. At an operational level, this will mean embracing increasingly autonomous security workflows offloaded to AI systems - handling tedious triaging and basic response while escalating only the most critical issues to skilled analysts for analysis and key decisions. It's a pragmatic balance of human and machine capabilities. We'll also need a new class of cybersecurity professionals fluent in interpreting AI system outputs and translating them into strategic guidance. These AI-savvy analysts must be adept at not just using but explaining and justifying AI system behaviors and decisions to leadership stakeholders. It plays a crucial role in building organizational trust and accountability around AI systems. Additionally, organizations must adopt secure AI system development lifecycles, proactively battling adversarial AI threats through approaches like robust model training, adversarial testing, privacy-preserving analytics, and defensive AI architectures. We simply can't leave our AI systems vulnerable to adversarial subversion. Thankfully, I see positive momentum towards these goals across the AI security startup ecosystem and cybersecurity community. But we must keep pressing forward holistically - investing in skilling our people, refining our processes, and pioneering new AI-centric technologies securely and ethically. Only then can we responsibly wield AI's incredible cyber defense potential without enabling worse nightmares. Despite all the work ahead, I'm hugely optimistic as an AI expert and founder. I've already deployed these transformative AI capabilities in the field, experiencing their game-changing impact firsthand. AI gives us a truly decisive advantage in combating even the most sophisticated threat actors - if we successfully fuse machine intelligence and human expertise. It won't be easy, but I'm convinced the payoff will be a safer, more secure digital world actively hardening itself against cyber threats in real-time. A world where novel attacks are neutralized before impact, where vulnerabilities are patched before exploitation, and where malicious insiders and compromised accounts are stopped in their tracks. Best of all, AI cyber defense done right should free up our human personnel for higher-impact strategic work, not tedious data grunt work. AI should empower us to be the cybersecurity experts, creative problem-solvers, and strategic leaders we always aspired to be - not menial attack analysts. So to my fellow AI professionals, founders, and innovators - the path ahead is clear. Let's blaze this trail TOGETHER, pioneering the new era of practical, intelligent, and ethical AI-powered cyber defense. The future of digital safety depends on us doing this right. And with our unique combination of human ingenuity and machine intelligence, I'm confident we're up to the immense challenge. Let's get to work.

Applications of Artificial Intelligence in Cybersecurity: Boosting Threat Defense System

Bias Leads to Intelligence Artificial Released from the corners of the boardroom for decision support, AI has now become a team player in the modern digital enterprise. And for the right reasons - according to a McKinsey survey, 66% of AI adopters report an increase in their revenues. Beyond money matters, AI can elevate the customer experience through various use cases. However, if done irresponsibly, AI wonders can quickly turn into AI disasters - and history is our accomplice in this observation. From introducing gender bias in hiring algorithms and racial bias in facial recognition algorithms to charging higher interest rates for underprivileged communities in loan decisioning use cases, AI disasters are commonplace and cost businesses more than just a few hundred million dollars, according to Harvard Business Review. Beyond the need for mitigating AI's downside impact on a business, building fair and responsible AI algorithms is as much a socio-ethical imperative for businesses that intend to stay in business. Take a look at how bias creeps into AI models and a framework to address bias in your enterprise AI strategy. Tracing Sources of Bias in Your AI Strategy Most enterprises have moved towards a standard framework for building business-driven use cases of AI. However, within the larger AIOps cycle, bias can creep into a model from any of the five stages that lead to the development of an AI model. Here are some of these sources: : AI models often make use of - consider a dataset of loan decisions, hiring decisions, or a list of buyers from a shopping mall. Bias within datasets datasets that carry the footprints of human bias within them Such datasets can inject bias into a model if their predictors are labeled erroneously, if certain types of communities are under-represented, or if the data sampling strategy was itself biased, to begin with. : AI models are built through extensive processes, which include feature selection, model tuning, and dataset splitting. Sometimes, excluding some features or conducting train-test splits without adequate oversight can inject data into the model. For instance, training a model with data from the earlier quarter of the year for a variable that follows an annual trend can lead to a biased model. Bias in model development : Some algorithms are prone to overfitting, while others are to underfitting. Again, understanding the model's needs from its real-world application can help data scientists identify the right level of complexity that minimizes the total error. Injecting bias during validation Moreover, preventing leakage between test and training data can be another source of bias during the model testing and validation phase. : NLP-powered bots that generate engagement and interaction within communities can pick biases from the humans they interact with. These algorithms can amplify the racial and gender biases that are to be found in the human voices on the platform. Acquiring interaction bias : Some models are biased in the very purpose they are built for. Consider the example of Google News, which returns similar stories when a user runs a search. Such programs can land the user in an information bubble built by the intent and parameters of their search query. Bias in purpose Recognizing the source of biases is the first step to building fair and bias-free AI models - followed by which enterprises should consider the following framework for mitigating bias from their AI strategy. A Roadmap to Achieving Fairness in AI Today, technical communities are making considerable efforts to mitigate bias in AI models. But three key levers are crucial to pay attention to. These include: Promoting responsible algorithm development, Doing standard checks during data collection and modeling, and Working with your CSR teams for responsible AI development. Look at these in detail, and consider checking out the hyperlinked resources for getting started. Promoting Responsible Algorithm Development The algorithm development process is prone to absorbing biased influences at multiple points. Here is a checklist for promoting enterprise-wide responsible algorithm development: Brainstorm the purpose of an algorithm, and optimize the point of equity-efficiency tradeoff collectively. Document the development process ( which teams are developing the model, potential risks of bias in the model, and privacy implications of the data used. here is a way to do that ), Hold meetings with developers to identify if an algorithm needs human oversight to mitigate risks of bias. Engage communities served by the system/algorithm, explain the model to them, and ask for their suggestions to improve model fairness. Conduct multiple audits on a developed model and provide the auditors with complete documentation. Lastly, promote explainability and run black-box auditing where design decisions and data models have been internalized into the algorithm. The above steps can help bring the risk zones into sight and mitigate bias-associated risks during algorithm development early on. Data Collection and Modeling: Standard Checks Data is the most significant source of bias in AI model building. Therefore, focus on data collection and modeling processes for eliminating bias, mitigating risk, and maximizing the business value of an AI model from the get-go. Consider the following steps for curating bias-free datasets across the enterprise: Run diversity and inclusivity tests on labels that describe datasets based on . comprehensive DEI lexicons like this one Document the sources of data and build checklists to identify possibilities of under or over-representation of a community. Define the standards for using third-party datasets by and implement guardrails to help developers follow these standards. leveraging data risk checkers Circulate comprehensive guidelines around what features are appropriate to be analyzed and before being used by a model in production. define privacy checks that a dataset should comply with Lastly, principles and processes to ensure responsible use of data should be internalized within the organization's data strategy. This can be achieved by enforcing technological guardrails that cannot be overridden by your users, and . using data from a variety of vetted sources Activate CSR for Responsible AI Development CSR teams often help an organization move the needle of equity across the larger fabric of society. Therefore, CSR teams can play a key role in advancing an organization’s responsible AI roadmap. Here is how to achieve this alignment: Shift CSR efforts towards the discourse of responsible AI and fund opportunities to develop novel ways of mitigating AI risks. Run CSR-driven programs to mitigate biases introduced by internal teams in building AI models. Market your efforts to the larger community. Lastly, create a symbiosis between CSR efforts and internal teams to align the organization's DEI vision to its efforts and generate employee engagement to foster holistic DEI thinking. Final Words The idea of bias and fairness is incomplete and therefore, evolving. Before embarking on the journey towards fair AI development, enterprises must acknowledge that their conceptions of fairness (and consequently bias) will be incomplete, too. But that is not a reason to sideline the question altogether. The promises of AI are abundant for businesses - that is, only if the technology is used in a responsible and socially and ethically conscious manner. By following the framework outlined above and leveraging responsible AI tools from hyper-scale technology providers, enterprises will be well-positioned to achieve holistically desirable outputs from their AI strategy.

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