As population continues to age, there is a growing demand for motor rehabilitation services

SWORD Health

The recent Cambridge Analytica and data scandal represents another in a long line of debacles by major companies charged with protecting the personal data of its users. The Equifax hack of 2017 is still fresh in the minds of some citizens, and though it’s not the same situation, there are still striking similarities between what happened with Cambridge Analytica and the misuse of Facebook data, and Equifax’s shameful lack of security protections. Facebook exactly The theme here is that big, faceless organizations have a lot of power and control over the data that average citizens take for granted — data that, sometimes, people don’t even realize they’ve given up. Not only that, but, in the case of Equifax’s data breach, some of this compromised information is “lifetime data,” things like Social Security numbers and patient health information that can’t simply be changed or replaced like a password can be. So, who pays when data is mishandled by giant global organizations? The user. You. Me. Basically everybody these gargantuan entities. but This needs to change. A Double-Edged Sword isn’t necessarily a bad thing on its own, nor is it really a new concept. Big data In their article, “ ,” the experts at GWU mention the government has collected data on patent, population, and weather since 1790. They also touch on the fact that businesses and healthcare facilities that collect big data can personalize their approaches to patients and customers, and in effect, make decisions that are both good for business as well as good for preservation of human life. How Data and Decisions Work Together Unfortunately, big data is a double-edged sword, and the healthcare industry is a perfect example of this. Doctors are able to use data to provide more accurate diagnoses and save lives, and there’s even a set of federal standards to protect patient data called the . Health Insurance Portability and Accountability Act (HIPAA) that “several HIPAA violations are common among health organizations, such as failing to store private health care information properly, failing to obtain written consent from patients and sharing photos of patients on social media.” Multiple sources confirm This is somewhat frightening news, considering that the healthcare industry has become the targeted industry of all, even beyond financial service providers. state that “EHR security breaches range from simple flaws in network security to determined, focused attacks maliciously orchestrated by expert hackers. In May 2017, a simple authentication flaw in Molina Healthcare’s network exposed up to 4.8 million patient records,” they write. “The exposed data included names, addresses, birth dates, diagnoses, and other medical information about individual patients…” most Duquesne University’s online resources Here’s the catch: HIPAA fines are steep and well enforced. Some reports have even come out showing that harsher penalties for HIPAA violations have been in the works. However, is this type of enforcement being shown to social media companies and credit bureaus? What ever happened as a consequence of the Equifax hack or the latest Facebook fiasco? A Surprising Lack of Justice So Far … For anybody that doesn’t remember, the hacking of Equifax’s consumer and financial data put at risk the personal information of up to 143 million Americans. published via The New York Times, Peter J. Henning writes that, naturally, many will wonder the legal consequences the company and its executives might face. In his article “The answer, for those who remember the government’s response to the financial crisis,” he writes, “will be as familiar as it is unwelcome: not much. That seems outrageous when so many individuals may see their identities stolen because of a company’s failure to ensure the safety of its primary product. But Equifax operates in a sphere with minimal government regulation, and its conduct is unlikely to trigger a criminal prosecution of the company or any of its executives.” As for Cambridge Analytica and Facebook, the former still has seen no charges against their firm, even though Brazil prosecutors into their activities. The latter also has yet to face consequences, with that Facebook CEO Mark Zuckerberg “confirmed that no employee was fired in the wake of the scandal because, in his words, it’s his fault: ‘At the end of the day this is my responsibility,’ he said.” have opened an investigation David Lumb from Engadget reporting Even the #deletefacebook movement and the abundance of bad press against Facebook hasn’t seemed to have made much of a dent in the social media giant’s bottom line. So how do we keep something like this from happening again? How can we ensure that more companies don’t abuse the inherent power that comes with ownership of so much data? It All Comes Down to You The frustrating thing is that all of this comes down to you, the user. The unfortunate reality is that the people charged with protecting our data and personal information — they’re not doing it. To top it off, the people that should be ensuring just penalties befall those that shirk data protections — they’re not doing their jobs either. This situation is complicated by the fact that many are confused by how these technologies work. However, that shouldn’t be an excuse anymore. Every citizen is faced with user agreements and other technological mumbo jumbo that the law says they know and follow … why should it be any different for politicians? Why shouldn’t politicians and data-abusers face consequences and be held to a standard of knowledge? must more higher I could sit here and say that we need more regulation, or that our leaders need to punish those responsible for playing us all like fools, but those things won’t happen. The bad news is, nothing is changing — not until the little guy finally stands up and says “I’ve had enough of this.” There are those fighting the good fight, and I applaud them. Perhaps it is they who will usher us toward a new era with responsible leadership. Until they, look inward. Realize that this issue affects every single one of us. Decide where you stand on the issue. At least that’ll be a start. Where we go from there? Nobody knows.

With Great Power Comes Great Consequence

We live in the age of technology, with almost every aspect of our routine life now relying on automated systems to function. The healthcare sector is no exception, being one of the areas to transform exponentially during the last decade. Electronic health records (EHRs) are the epitome of this change, with the majority of hospitals relying on this feature. However, healthcare organizations and hospitals around the world face the same issue: what should be done with this when the system no longer needs it? You cannot just throw the data away, so what could be the best solution to this problem? vast amount of data Data Archiving The best solution is data archiving. Data archiving is , such that it is no longer directly connected to the system but can be accessed for future reference. Archiving prepares and stores the data for long-term retention, as the data, while not in use today, can be needed for legal or regulatory compliance reasons in the future. the process of moving data to a separate storage Why Archive? Archiving has a lot of advantages. One of the greatest benefits is that archiving data reduces storage costs. This is especially true for primary storage, which is very expensive due to its quick read–write ability to ensure timely operational requirements. Archiving provides a cost-effective solution since the storage used is capacity-centric and usually low-performance because it is rarely accessed. A study conducted on the financial aspects of the healthcare sector revealed that 85% of healthcare units have seen financial gains after shifting to data archiving due to reduced maintenance and better encryption. Another major benefit of archiving is that it eliminates data duplication. Archiving reduces the overall spread and volume of data by removing duplicate data sets. Data that is infrequently accessed is also removed. This reduces the overall storage footprint while keeping storage costs in check. There are many other indirect benefits of data archiving as well that might prove beneficial for any healthcare sector in the long run. Some of these benefits include: Archived inventory forms an active cloud legacy data repository to satisfy regulatory requirements. Data storage in EHR can be used by analytic tools to view trends in order to enhance research for better patient care. Archiving data provides an alternative to maintaining legacy data books, greatly reducing operation costs and HR requirements. Encryption provides up-to-date protection, securing your archived data and mitigating data breaches. Backup vs. Archiving It should be noted that data archiving is not the same as data backup. A backup involves copies of data whose main purpose of storage is data protection and recovery. This is actually a spare set of data that can be used to rebuild the original database in case of data corruption or loss. An archive, although using the same storage mechanism as a backup, involves reducing data for data retention purposes. It is actually a repository for infrequently and rarely accessed data. AI-Powered Ransomware & the Healthcare Sector Ransomware and unethical hacking are among the tragedies that exist in the tech sector. Ransomware is a type of malware that affects the system data and renders it useless. In order to return the data, the hacker involved demands a ransom. The healthcare sector’s shifting of massive amounts of data online makes it a prime target for these ransomware attacks. Additionally, the advent of artificial intelligence (AI) in recent years has greatly increased these attacks on the healthcare sector. In 2019 alone, data breaches cost . healthcare organizations over $4 billion The usual targets of these ransomware attacks are healthcare units using outdated tech and encryption methods to secure their data. The old JBoss[ii] server software is the major gateway for these hackers to access hospital servers. Recently, a hospital in California was rendered crippled by one of the most devastating cyber attacks. The hospital paid a total of $17,000 to gain access to their files and resume operations. Fortunately, AI can be used as a double-edged sword for the benefit of the healthcare sector as well. AI encryption technologies can be used to provide high-level security to keep vast amounts of data on servers safe. Many healthcare units use these tactics to ensure the safety of their patients’ data. Bumrungrad International Hospital is one such healthcare provider that strives to provide you with the best healthcare facilities while keeping up-to-date with the tech sector and ensuring full encryption of their patients’ information. Final Words Data archiving provides an easy solution to the data storage needs of the . However, huge amounts of data stored on low-tier drives can make them an easy target for ransomware attacks. To ensure the safety of user data, data encryption and AI security measures can be explored as viable tactics against these attacks. Many healthcare units around the world have started to adopt these advanced measures, and many are also in line. Needless to say, the healthcare sector is truly transforming! healthcare sector around the globe

A Quick Take on Data Archiving for the Healthcare Sector

In the realm of high fashion, Tom Ford stands as an icon, renowned for his exceptional talent and innovative contributions to the industry. Beyond the glamour of the runway, however, lies a complex narrative that intertwines with the broader discussion of mental health. This article delves into the life and career of Tom Ford, exploring the profound impact of his work on the fashion world and how his journey reflects aspects of mental health. I. Tom Ford: A Visionary in Fashion Tom Ford's name is synonymous with luxury, sophistication, and a distinctive design aesthetic. Born on August 27, 1961, in Austin, Texas, Ford's journey into the fashion world began with his studies at the Parsons School of Design in New York. His career trajectory saw significant milestones, including positions at renowned fashion houses such as Gucci and Yves Saint Laurent. Ford's groundbreaking work at Gucci, where he served as creative director from 1994 to 2004, revitalized the brand and positioned him as a trailblazer in the fashion industry. Ford's approach to fashion goes beyond creating clothing; it's about crafting a lifestyle. His keen eye for detail, emphasis on sensuality, and commitment to pushing boundaries have made him a transformative force in the industry. The intersection of creativity and mental well-being becomes apparent when examining the intense pressures and relentless pursuit of perfection that often characterize the world of high fashion. II. The Demands of the Fashion Industry and Mental Health The fashion industry, with its fast-paced nature and ever-evolving trends, is notorious for its demanding and competitive environment. Designers like Tom Ford, operating at the pinnacle of this world, face immense pressure to continuously innovate and deliver collections that captivate audiences. The creative process itself can be mentally taxing, requiring a delicate balance between artistic expression and commercial viability. The toll of such pressures on mental health is a pervasive issue in the fashion world. Designers often grapple with anxiety, burnout, and the constant quest for validation. Tom Ford, in his various interviews, has hinted at the challenges he faced during his tenure at Gucci, where the relentless pursuit of success sometimes overshadowed personal well-being. This reflection opens a window into the nuanced relationship between creative brilliance and the toll it can take on an individual's mental health. III. Tom Ford's Advocacy for Mental Health Awareness In recent years, there has been a growing awareness and destigmatization of mental health issues across various industries, including fashion. Tom Ford, with his characteristic candor, has been an advocate for mental health awareness. In interviews, he has discussed the importance of acknowledging the challenges faced by those in the creative fields and the need to prioritize mental well-being. Ford's openness about his own experiences navigating the pressures of the fashion industry contributes to a larger conversation about the intersection of creativity, success, and mental health. By sharing his story, Ford encourages a more compassionate and understanding approach to the struggles faced by individuals in the pursuit of their passions. IV. Creativity as a Double-Edged Sword While creativity is celebrated in the fashion world, it also poses a unique set of challenges for those who wield it. The intense creative process, coupled with the expectation of constant innovation, can lead to periods of self-doubt and vulnerability. Tom Ford's career trajectory, marked by both triumphs and moments of introspection, exemplifies the dual nature of creativity as a powerful force and a potential source of internal conflict. Exploring the intricacies of this duality, it becomes evident that fostering a supportive and empathetic environment within the fashion industry is crucial. Recognizing the humanity behind the creative genius is not only beneficial for individual mental health but also contributes to the overall sustainability of the industry. V. Conclusion: Navigating the Intersection of Creativity and Mental Health In conclusion, Tom Ford's journey through the world of high fashion serves as a compelling narrative that extends beyond the glamour of the runway. His impact on the industry is not only measured by the success of his designs but also by the candid discussions he fosters regarding mental health. As we celebrate the creative brilliance of individuals like Tom Ford, it is essential to acknowledge the complex relationship between creativity and mental well-being. By unraveling the layers of this intersection, we pave the way for a more compassionate and understanding approach to the challenges faced by those who shape the world of fashion and, by extension, the broader creative landscape. Also published . here

Tom Ford's Influence on Fashion, Creativity and Mental Health

Team Ninja’s Nioh 2 is one of the hardest games out right now. Its mixture of punishing Souls-like gameplay and complicated, interlinked mechanics comes together to create a hard but satisfying mix. Understanding the intricacies of the 11 Nioh 2 weapons and their skill trees aren’t just necessary to succeed, choosing two weapons to start with is one of the steps of character creation. Fortunately, this article is here to break down how to differentiate each weapon type and, more importantly, highlight how they feel, ensuring that the weapons fit your character’s look. After all, system makes imitating characters from other series really easy. Nioh 2’s Character Creation It’s also worth noting that weapon damage scales with where levels are allocated. While the game explicitly indicates the primary stat that drives a particular weapon’s damage, weapons scale off two other stats. For example, the Sword scales best with Heart but also scales with Strength and Skill but not as well. Sword Scaling: Heart, Strength, Skill It’s hard to imagine any kind of fantasy game that doesn’t have a sword. It’s equally hard to imagine a game set in The Warring States Period without katanas. In the game, it’s a reliable weapon that is squarely average in all areas. It does, however, have multiple skills that allow you to use Iai Quickdraw, a stylish attack that can deal massive damage in an instant. Not only is it fantastic for cosplaying Zenitsu from Demon Slayer, one of the mid-game sword skills makes it possible to chain Iai Quickdraw with blocks. Dual Swords Scaling: Skill, Heart, Strength If one sword isn’t enough, there’s always the option of having two. While this weapon type isn’t as versatile as the Sword, it encourages parrying more, by providing a damage boost on successful parries with the Heavenly Flow skill. It does also have some solid area of effect attacks with its high stance active skills. Dual Swords also encourage sustained attacks by giving a damage boost for maintaining a barrage of attacks which encourages a break from the staccato combat in Souls-like games. Odachi Scaling: Strength, Stamina, Heart To the uninitiated, an Odachi is essentially a greatsword from western RPGs. It’s a two handed, slower and more deliberate version of the Sword, at least at the start. Once some skill points are invested into its skill tree, the Odachi is great for dealing a lot of damage in a short period of time with skills like Twin Moons. The Waking Winds and Sunset Breeze skills allow Odachi users to switch quickly between stances to give it some fluidity. In contrast, some Odachi skills can trade movement speed for either ki regeneration or increased defence which does play a large part in its slower, more deliberate playstyle. Spear Scaling: Constitution, Strength, Skill The Spear acts exactly how one would expect it to. It’s a reasonably quick weapon that can struggle when dealing with multiple enemies. However, it’s got the longest reach out of the Nioh 2 weapons since it’s a pointy thing on the end of a long stick. That reach helps its users prod enemies from a relatively safe distance. Its shortcomings at dealing with groups with enemies can be mitigated with active abilities. Also, its attacks use up quite a bit of stamina which is worth keeping in mind. Axes (and hammers) While axes and hammers share the same skill tree, their stats work differently. Relative to axes, hammers deal less health damage and more ki damage. They also scale differently. Axe scaling: Stamina, Courage, Strength Hammer scaling: Stamina, Constitution, Courage The Axe weapon type is a great offensive pick for dealing with crowds. Attacks are slow, lumbering, and take up a lot of ki, which makes it hard to play defensively. That said, most of its attacks are able to hit multiple enemies, even ones that target single enemies as the animations often include a wind-up sweep that has the potential to hit. Like the Odachi, these weapons have abilities that can trade movement for effects. In this case, movement can be traded for defence or raw damage. Tonfa Scaling: Courage, Constitution, Dexterity The tonfa are a fairly unconventional weapon type. They excel at creating long, ki-draining combos that make it easy to stun enemies. The early game shove skill allows them to easily deplete enemy ki reliably. The Demon Dance skills let users dodge on ki pulse which is fantastic when used defensively though it's hard to break the muscle memory that the other weapons build. Kusarigama Scaling: Dexterity, Skill, Strength Kusarigama essentially boil down to a metal ball and a sickle connected by a chain. Naturally, this sort of unconventional weapon design translates well into gameplay. Kusarigama can alternate between long-reaching attacks and short-range fast swinging ones based on stance. The skills available to the Kusarigama take advantage of this to allow users to reel enemies in and allow some truly fast attacks. The speed this weapon type is capable of allows it to easily apply status effects to enemies. Considering that it scales well with Dexterity, which strengthens Ninjitsu, this capability makes it helpful to ninja builds. Hatchets Scaling: Skill, Courage, Magic One could be forgiven for thinking that Hatchets are a ranged Nioh 2 weapon. Its skill tree is chock full of skills that involve throwing the hatchets in some way. In actual combat, they work well in blocking and breaking enemy blocks but it’s the throwing that makes them truly unique. Hatchets work fine in melee and can easily stretch out to strike targets further away. It’s also really helpful in luring enemies away from a pack without using valuable ammo to do it. Fists Scaling: Strength, Heart, Dexterity The Fists work similarly to the Tonfa. Instead of dealing high damage on each hit, Fists excel at wearing down enemy ki to open them up for finishers. However, Fists take combos to the next level. The Unbroken skill encourages such play by increasing damage based on the number of active skills used consecutively while allowing forward movement during a ki pulse. Letting out a barrage of attacks to weaken enemies makes Fists incredibly fun to use if very skill heavy. Switchglaive Scaling: Magic, Constitution, Skill Switchglaives are easily the least realistic Nioh 2 weapons. This weapon is based around transforming from three different weapon forms that change with stances. Each transformation plays to the strength of the stance. Low stance helps with dodging and disengaging. Mid stance can stun and block and high stance deals damage. Switching between stances is incentivised by being able to change mid combo which makes this weapon type incredibly adaptable. Splitstaff Scaling: Magic, Courage, Strength A Splitstaff is basically a pair of nunchucks glued together and used as a bigger stick. Like the spear, it has excellent reach and ki-hungry attacks that make managing ki a big part of its build. What helps it stand apart from the Spear, however, is its ability to split open into its halves. Abilities that draw on that characteristic further extends the Splitstaff’s range while striking rapidly, making it great for applying status effects. Final Thoughts on Nioh 2 Weapon Selection The weapon choices available in Nioh 2 is one of the game’s most impressive aspects.Having an idea about how each weapon works might ease a new player into the game. I hope this guide helps you throughout your Nioh 2 journey!. Also, be sure to check out 5 Best Pokémon Games of All Time Ranked MASS Builder Review: The Mech Game You've Never Heard of Resident Evil Village Launches on May 7, Multiplayer Re:Verse Experience Announced

Nioh 2 Weapons Guide: From Sword to Switchglaive

_You might have heard people say something like “data is the new oil”. This phrase captures the fact data is now a highly valuable commodity. But how does the value of data impact personal privacy? This article explains the central threats to privacy inherent in how data is stored and shared on the internet, and how blockchain technology can eliminate these threats. It also addresses an issue that is not receiving enough attention from blockchain enthusiasts, which is the privacy problems that immutability create_s. Data is a Valuable Commodity In the past few years, individuals using digital technologies have generated vast amounts of data. 2.5 quintillion bytes of data are generated each day by individuals browsing the internet, interacting on social networks, using mobile phones, uploading personal files, syncing devices, shopping online, etc. To get a sense of the volume of this data consider that in 2017 the rate of stored data grew than the world economy. The rate at which this data is accumulating is growing exponentially. Forbes that 90% of the world’s data was created in the last 2 years alone. This data mass is a significant source of value and power for those who control it. 4x faster reports The fact that control of personal information is monopolized by private entities is a problem. The individuals who actually generate the data do not benefit from its value. Users lose control over personal information when signing up to services like Facebook, Google, Instagram, Twitter etc.. These platforms offer free services in exchange for data. Tracking individual likes and dislikes, desires, searches, and life choices has huge value for advertisers. Large private organizations own the data and store it in huge silos where it is bought and sold to advertisers. It is also vulnerable to tampering and theft. However, the individual loss of control of personal data actually goes much deeper than just a few companies that currently monopolize it. It lies in the very structure of the internet itself. The Deeper Threat to Individual Privacy The phrase “data privacy” often refers to rules set by centralized platforms that determine who has permission to access data and who gets informed when it happens. Yet, this is only the surface of the issue. The deeper threat to privacy lies in the way the internet itself works. The internet essentially operates like a massive copy-and-paste machine — copying information from one computer and pasting it to another. Not only do we have to repeatedly fill out forms every time we interact with a new organization or business. Those entities make store copies of our information in centralized databases that are easy targets for hackers. Every time we provide information to another online service, our private information is copied again. Every time this data is sold to an advertiser another copy is made, and so and so on. The architecture of today’s internet and personal privacy are incompatible. The solution does not lie in simply giving users the ability to control how platforms use their information. The problem requires a fundamentally new technological approach, one that handles information in a different way. I am not alone in thinking blockchain technology could provide such an approach. However, there are limitations that must also be addressed. In what follows, I describe the potential of blockchain technology to improve data privacy and the new challenges it also presents. Photo by hyku Blockchain Privacy Solutions The benefit of blockchain-based privacy platforms is they store personal data on a distributed ledger and give individuals control over who/what has access to it. Instead of making copies from one computer, the blockchain involves a transfer of ownership of the original information. This is very different from the way the internet works. Instead of sharing our data, again and again, there is one permanent record on the blockchain. We can give businesses and other entities temporary permission to access this data when needed. The blockchain effectively acts like a ticketing system, keeping track of who gets access, without revealing the data underneath. Immutability is a Doubled-Edged Sword Blockchains are “immutable.” This means information cannot be altered or removed without being noticed. While immutability is good for data privacy, it also presents two main challenges: Immutable storage of data is potentially in conflict with new information storage laws, like the (GDPR) in Europe. General Data Protection Regulation There is no way to correct inaccuracies on a blockchain — even if they are rare — because they are immutable. The Right to Erasure The GDPR has enshrined the right to erasure in law in Europe. It means individuals can request to have certain personal information “erased” from the internet if they choose. In a blockchain environment, however, erasure is impossible because the system is designed to prevent it. There is a discussion about is still open to debate. Some data protection authorities have found irreversible encryption could constitute erasure. For instance, a smart contract could revoke all access rights, thereby making the information invisible to others. what the right to erasure means in the context of blockchain While smart contracts may be able to address the right to erasure (though this is far from certain), they do not address a scenario where data is inaccurate. Immutability means mistakes cannot easily be corrected. This means individuals whose personal data is recorded incorrectly or fraudulently could face serious problems. Thus, in many instances immutability is a benefit. However, there will inevitably be instances where it also poses a problem. Governance mechanisms are necessary to deal with errors, fraud, or bugs in smart contracts. Startups Trying to Solve Privacy Threats Multiple companies are trying to develop the potential of blockchain technology for protecting privacy. is developing a blockchain-based network it says will have “unbreachable data protection”. is developing a personal identity verification protocol to manage digital identities. is working on making it easy for individuals to access, control, and share valuable health and personal information. The is developing a decentralized storage network and personal data marketplace. Shyft Civic Aenco Datum Network As interesting as these solutions are, none seem to squarely address the immutability problem. For example, Datum lets anyone store personal data securely and earn tokens for sharing it with pre-screened partners. Users will be able to see all transmitted data and trace who accessed it. Datum itself does not control the data and cannot access it. This is in stark contrast with the corporate silos that collect vast amounts of data under restrictive licensing terms. However, Datum does not have an answer to the immutability problem. The whitepaper states the network will initially rely on buyers for validation and regulation of fake data. This is not adequate. Realistically, there is no way for data buyers to verify information. Datum also plans to implement a trust ranking system. How it plans to correct errors in personal data is not explained. Conclusion More stringent government regulation of the data industry globally is on the horizon. Well-crafted regulations are welcome. However, startups are already starting to offer tools for individuals to take control of their data without appealing to state-based legal systems. The more users such platforms attract the more powerful the momentum becomes. If a critical mass of users started using these alternative solutions they could insist data be stored and handled through blockchains. At the same time, however, immutability stands in the way of conforming to the GDPR. It also poses a problem for correcting errors in personal data profiles.

Immutability is a Double-Edged Sword: Blockchain and Data Privacy

I suspect that there’s a certain personality type that is drawn to . The type of person that must be solving problems and learning new things, because without this drive, it’s hard to get ahead. But this career drive can be a double-edged sword, making it difficult to maintain a balance in life and prevent long-term damage to one’s health. programming The secret to gaining 20 lbs When I got my first real job at a Rails consultancy, there were a few lifestyle changes that came along with the new job that I didn’t pay much attention to at first, but over time had insidious consequences. For one thing, I now had a decent paycheck. I also didn’t have much free time anymore. So I started getting my meals from nearby restaurants rather than cooking, stopping off most evenings on my way home to polish off half a pizza. coding At the time I didn’t even realize I was gaining weight. And I didn’t know enough about nutrition to predict that eating half a pizza would have this effect. Sure, my parents raised me to eat healthy, but I was never a fat kid — or a very athletic kid — so I never gave nutrition much thought. It just dawned on me at some point that I had some serious back flab. Well I was alarmed. I was in bad physical shape and my mood was all over the place. Years later I would also realize that the intense tiredness that I felt every evening was a result of eating so much carbohydrate at once. Somehow it had escaped me that what I ate would have such a strong effect on how I felt. As a reflexive instinct, I began reading up as much as I could on nutrition. I learned what macro and micronutrients were, looked into the causes of weight gain, and began to understand how to eat in a way that would minimize my susceptibility to disease. I found that reducing my carbohydrate intake had a strong stabilizing effect on my mood and also kept me less hungry throughout the day, so I ended up adopting this way of eating. It took a few sluggish weeks to adapt, but I found the benefits worthwhile. Exercise and Movement Fast forward a few years, and my diet is in check. I now have the energy to do more activities, and I start wanting to look better as well. So I discover the joys of exercise. I get into salsa dancing and bodyweight fitness takes a prominent place in my life (unpaid shoutout to , which has really opened my eyes on the subject of calisthenics, bodyweight training, and flexibility.) Things start getting better health-wise. GMB But programming doesn’t get any easier and I’m still investing a ton of time into my career. I sit slouching at my desk for hours on end and when I start experiencing constant arm pain as a result of a bad ergonomic setup, I don’t worry too much since the pain usually goes away when I step away from the computer and head home. (Sound familiar?) So the cycle continues. I tolerate the slouchiness and lack of movement during the day, assuming that a little pain doesn’t actually harm you — it’s just uncomfortable. But this time the effects of bad posture did a number on me, one that can’t be remedied as easily as losing a few pounds. Long term damage A couple months ago I attempted a type of handstand that I was not prepared for and ended up with a bulging spinal disc in my neck. Very painful indeed. However, the radiologist who read my CT scan also broke the news that I had spinal degeneration that wouldn’t be atypical for someone twice my age. My years of slouching had caused permanent damage. It wasn’t a death sentence and most of the time it wouldn’t affect my life, but to me it was shocking that I had already built up years of damage to my body. In my mind, I was just starting to workout and learn how to use it. Go against the grain Some people may not have the luxury of working while taking proper care of their health. But if you live in a decent economy, ask yourself what you actually gain by living in that economy, if not the ability to maintain your health? After all, jobs come and go — but you only have one body in this life. The fact is, it can be hard to make the changes necessary for taking care of your health. Most programmers can’t really choose their office chair, or the height of their desk. Nor is it simple to get up and move a whole lot during the day when there is so much work to get done. And remote work can be difficult to find and perhaps lonely for some people. The reality is that prioritizing your health can sometimes require a complete overhaul, rather than just a micro change. It could take a lifestyle change to do what you need to do in order to live life the way you believe is best for you. A good method for making these changes is to think about what your own priorities are in a job. This can be scary because it can require you to go against the grain and say no to a job that others want, but which goes against your personal priority list. But choosing a job that matches your own personal priority list ultimately leads to greater job satisfaction as well as happiness in all areas of your life. Why do we neglect our health? Things like healthy food, exercise, and movement, are critical to all animals — not only humans. If it’s clear that dogs require daily exercise, why would a human, with its relatively enormous brain, be able to manage without it? And if we’re careful about the fuel that we put into our cars, why are we so lackadaisical about what we put into our bodies, a machine that has far more complex biochemical demands? I think the answer is that the human machine appears on the surface to be a forgiving one. It can temporarily compensate for shoddy fuel and shoddy treatment. These mechanisms are so clever, in fact, that we just continue feeding ourselves garbage and treating our bodies like garbage, not noticing that underneath the surface we are causing ourselves real damage. The good news is that prioritizing your health will give you benefits in all areas of your life. You’ll feel better, your future self will feel better, and all those around you will thank you for being less moody, more forgiving, and generally humbled by the work required to stay healthy.

The sacrifices we make to our health as programmers

Photo by on James Pond Unsplash Mentoring is the ability to give advise or train someone, often times, who is less knowledgeable in a particular field. This is pretty much common place in tech companies. There you usually have senior developers who, besides being a technical stronghold, use their time and skill to bestow their knowledge and enhance the skills of the less qualified developers. Mentoring has become quite a rite of passage where nowadays, you are looked upon to be a mentor, regardless of the position in your company. Most companies never state this as a prerequisite to getting a job, but it is well hidden by the all too familiar requirement of being “a team player”. A mentor doesn’t specifically have to be someone who has a ton of experience or a strong grasp over as many fields as possible. You can become a mentor by being the developer who recently delved into a specific section of code that not everyone is aware of or by taking ownership over a certain concept. While it may seem like mentoring is a win-win situation, where both sides benefit, the reality is quite the contrary. Photo by on James Pond Unsplash Why Mentors Are Rare Mentoring is not a teachable trait, and it is very rarely something that can be inspired in people. You either have it or you don’t. Some people may want to become mentors or state they are, but they lack the minute details of what it means. If you do not know how to approach different people or you don’t possess the ability to pass knowledge down in a constructive manner, being a mentor is not something you should consider. For these reasons, people who other people consider as mentors are few and far apart. That is why, in part, most organizations try to distill in their workers the spirit of mentorship. Don’t give companies too much credit though. While it may seem like companies are working to spread mentoring around to help drive workers in a professional way, there is another aspect to look at. When you have only one person which holds information about a specific feature, which is sometimes referred to as “heroes”, you are at a risk of a substantial loss of knowledge when that person leaves. With mentorship, instead of having one person who holds crucial data about the product that everyone leans on, you can spread that knowledge around. Creating a more stable foundation in case of an earthquake. Photo by on Jerry Wang Unsplash What drives people to become mentors No one is truly altruistic, but in our day to day lives, we tend to want to help others around us. Some more than others, but the general principle is . The same thing applies in our jobs, where we are confronted with daily opportunities to abide by that saying. “do unto others as you would have them do unto you” Most people who see themselves as mentors, look at their fellow colleagues and see in them a past version of themselves. Meaning, they see themselves when they were less skilled and less capable and remember how they yearned for some guidance. Some of them where actually mentored by someone, lighting the fuse that ignited their will to become a mentor. But some just realize they want to be that person who helps people evolve and advance professionally. Mentors actually enjoy seeing their surrounding becoming better at what they’re doing and in part, support a healthy working environment where people aren’t only defined by their specific position. This satisfaction is a key part in why people become mentors, but it is also the Achilles heal that can bring them down. A Perfect World In a perfect world, mentors would be the most popular people in their group, receiving the highest salaries and getting the respect they deserve. But as far as company culture goes, it’s survival of the fittest. In today’s world, you are measured only by your proficiency and efficiency. This leads to constant power struggles where people are fighting to advance their career and level up in the company’s job ladder. Due to this and in combination with inner politics, mentors are usually the ones holding the short stick. Mentors are nurturing the people around them, but are not necessarily being taken care of professionally. Because of this, certain situations can arise where mentors are basically digging their own way out of the company. Take this scenario as an example: Consider a team of developers, where one of them is a senior. Let’s say that the senior developer is a mentor to the other less experienced ones and over time, allows them to become more knowledgeable and proficient. At some point, they will want to advance in their careers, while the senior is glued to his/her status. Looking at things from a financial standpoint, their boss will have an option between keeping the more expensive senior developer, or promoting a developer who will cost less money and have the same level of knowledge. If you were their boss, what would do? you Photo by on On CloudVisual Unsplash A Personal Note The reason behind writing this article comes from my fair share of moments where being a mentor to the people around me, backfired. Now you could say that I was surrounded by crummy people or that I may have done something to antagonize them, but the reality couldn’t be more opposite. The backdrop behind this lies in the fact that I was relatively new at the company I started working at, but I had already received significant praise and responsibility others did not. This obviously shone a light on me, making others aware of my situation and infusing them with doubt about their standing in the company and their career. While not being a senior developer, I was one of the few native developers around, and I took more interest in training and building the people around me than other people did. This was not common in my workplace and increased the size of the target on my back. In one case, I was helping a fellow colleague who got stuck on a certain issue he couldn’t fix. He called me over one morning asking for help and proceeded to tell me how he has approached almost everyone in our team and division to help him out, but they all failed to solve his issue. Let’s leave behind the fact of how he decided to make note of everyone he talked to and how I’m the last one in the pecking order. Cut to fifteen minutes later, his problem is solved, and I am investing time in explaining to him why the problem occurred and how to overcome it in the future. While I am sitting there helping him out, his team has their morning routine of discussing what they are doing. I stay and I hear how the developer mentions everyone who has tried to help him, but he decides to leave me out. . Coincidence? I think not Don’t forget the fact, that I am still sitting there, solving his issues. I confronted him a day later about it and he offered in return a lame excuse. He said he didn’t think about it, saying he was preoccupied in naming all the people who tried to help him out and couldn’t focus on who actually did help him. This might seem like a small incident that I’m fussing way too much about, but this person always failed to mention me when giving credit, while still giving credit to other people. If at first I thought this was a one off incident, as time progressed, there were more instances where people either failed to give me credit or took ownership of things that I did. A year later there came an opportunity to apply for a team leader position in our group. Subsequently, I was running up against him. Who do you think got picked? In failing to recognize my abilities and mentioning me to superiors, he essentially blocked off my career path, while advancing his. There were numerous occasions where I had my superiors say to me that they have not seen me do something. Whether it be leading people around me or promoting soft social skills. But in truth, those stuff happened, but were not communicated upwards by the people with whom I had done so. Now, I believe the developer I was up against thought of all this and deliberately acted this way. Since he had his goals set on showing how he is progressing professionally to allow him to become the better candidate for the team leader position. I cannot emphasize in words how much this hurts, both emotionally and spiritually. You are putting yourself out there, with the will and conviction of helping others, for reasons that are far from egotistical, but you are constantly reminded of the bad character in humans. You begin to have doubts about your co workers and how your daily interaction with them is just a facade. As much as it is horrible to undergo all of this, I haven’t given up on mentoring people. I still feel immense satisfaction from teaching people and watching them grow. You could say I’m a sucker for helping people, but I would rather have it this way, than acting like everyone else.

How Being A Mentor Can Be A Double Edged Sword

We see that multiple industries are working hard to accelerate the adoption of Artificial Intelligence, without having the proper security measures in place. It is important to know that AI is not some invincible new technology, but rather, a technology extremely vulnerable to cyber threats just like many others that came before it. The motivations for attacking AI are what you would expect. They range from financial gain to manipulating public opinion to gaining competitive advantage. While industries are gaining the benefit of increased efficiency and innovation thanks to AI, there is still the concerning reality that expanding the use of AI causes a significant increase in security risks. Risks Related to the Use of AI Like with any other life-changing technology, artificial intelligence is a double-edged sword. Although it’s already starting to have a massively positive impact on our lives and workflows, it also has tremendous potential to cause serious harm, especially if used carelessly or with overt malicious intent. There are plenty of ways in which adversaries - such as criminals, terrorists, cyber threat actors, foul-playing competitors, and repressive nation-states can utilize AI to their advantage. There are also numerous obscure risks related to the legitimate use of this technology. Privacy is also an issue when it comes to the information we share with AI-based tools. Data leakage can cause significant legal issues for businesses and institutions. In addition, because of code generation tools, vulnerabilities could be introduced into the software - intentionally, by poisoning the datasets, or unintentionally, by training the models on already vulnerable code. All this is on top of copyright violations and various ethical and societal concerns. Generative AI is especially vulnerable to abuse. It can be: a) manipulated to give biased, inaccurate, or harmful information b) used to create harmful content, such as malware, phishing, and propaganda c) used to develop deepfake images, audio and video d) leveraged by any malicious activity to provide access to dangerous or illegal information. There’s a lot of conversation about the safe and ethical use of AI-powered tools, however the security and safety of AI systems themselves are still often overlooked. It’s vital to remember that, like with any other ubiquitous technology, AI-based solutions can be abused by attackers, resulting in disruption, financial loss, reputational harm, or even risk to human health and life. There are, broadly, three types of attacks targeting AI: Adversarial machine learning attacks - Attacks against AI algorithms, aimed to alter AI’s behavior, evade AI-based detection, or steal the underlying technology.
Generative AI system attacks - Attacks against AI’s filters and restrictions, intended to generate content deemed harmful or illegal.
Supply chain attacks - Attacks against ML artifacts and platforms, with the intention of arbitrary code execution and delivery of traditional malware. Securing Your AI for Better Data Security Understanding and implementing extensive security measures for AI is no longer a choice. It’s a necessity. Too much is at risk for organizations, government, and society at large. Security must maintain pace with AI to allow innovation to flourish. That is why it is imperative to safeguard your most valuable assets, from development to operation and everything in between. Discovery and Asset Management First, identify where AI is already used in your organization. What applications has your organization already purchased that use AI or have AI-enabled features? Second, evaluate what AI may be under development by your organization. Third, understand what pretrained models from public repositories may already be in use. Risk Assessment and Threat Modelling First, conduct a benefit assessment to identify the potential negative consequences associated with the AI system if those models were to be compromised in any way. Second, perform threat modeling to understand the potential vulnerabilities and attack vectors that could be exploited by malicious actors to complete your understanding of your organization’s AI risk exposure. Data Security and Privacy Go beyond the typical implementation of encryption, access controls, and secure data storage practices to protect your AI model data. Evaluate and implement security solutions that are purpose-built to provide runtime protection for AI models. Model Robustness and Validation Regularly assess the robustness of AI models against adversarial attacks. This involves pen-testing the models’ response to various attacks such as intentionally manipulated inputs. Next, implement model validation techniques to ensure the AI system behaves predictably and reliably in real-world scenarios. This will help minimize the risk of unintended consequences. Continuous Monitoring and Incident Response Implement continuous monitoring mechanisms to detect anomalies and potential security incidents in real time for your AI. Require your vendors to utilize AI in their solutions to alert you to attacks that could compromise your data or business processes. Develop a robust AI incident response plan to quickly and effectively address security breaches or anomalies. Regularly test and update the incident response plan to adapt to evolving AI threats. Conclusion The security landscape as well as AI technology are dynamically and rapidly changing. It’s crucial to stay informed about emerging threats and best practices. Regularly update and refine your AI-specific security program to address new challenges and vulnerabilities. Responsible and ethical AI frameworks in many cases fall short of ensuring models are secure before they go into production, as well as after an AI system is in use. Always ask yourself the following questions 1) What am I doing to secure my organization’s use of AI? 2) Is it enough? 3) How do I know? Only by answering these questions with data-driven, intellectual honesty, can you maintain the integrity of your security role and keep your organization secure. We see that multiple industries are working hard to accelerate the adoption of Artificial Intelligence , without having the proper security measures in place. It is important to know that AI is not some invincible new technology, but rather, a technology extremely vulnerable to cyber threats just like many others that came before it. The motivations for attacking AI are what you would expect. They range from financial gain to manipulating public opinion to gaining competitive advantage. While industries are gaining the benefit of increased efficiency and innovation thanks to AI, there is still the concerning reality that expanding the use of AI causes a significant increase in security risks. Artificial Intelligence Risks Related to the Use of AI Like with any other life-changing technology, artificial intelligence is a double-edged sword. Although it’s already starting to have a massively positive impact on our lives and workflows, it also has tremendous potential to cause serious harm, especially if used carelessly or with overt malicious intent. There are plenty of ways in which adversaries - such as criminals, terrorists, cyber threat actors, foul-playing competitors, and repressive nation-states can utilize AI to their advantage. There are also numerous obscure risks related to the legitimate use of this technology. Privacy is also an issue when it comes to the information we share with AI-based tools. Data leakage can cause significant legal issues for businesses and institutions. In addition, because of code generation tools, vulnerabilities could be introduced into the software - intentionally, by poisoning the datasets, or unintentionally, by training the models on already vulnerable code. All this is on top of copyright violations and various ethical and societal concerns. Generative AI is especially vulnerable to abuse. Generative AI It can be: It can be: a) manipulated to give biased, inaccurate, or harmful information b) used to create harmful content, such as malware, phishing, and propaganda c) used to develop deepfake images, audio and video d) leveraged by any malicious activity to provide access to dangerous or illegal information. There’s a lot of conversation about the safe and ethical use of AI-powered tools, however the security and safety of AI systems themselves are still often overlooked. It’s vital to remember that, like with any other ubiquitous technology, AI-based solutions can be abused by attackers, resulting in disruption, financial loss, reputational harm, or even risk to human health and life. There are, broadly, three types of attacks targeting AI: There are, broadly, three types of attacks targeting AI: Adversarial machine learning attacks - Attacks against AI algorithms, aimed to alter AI’s behavior, evade AI-based detection, or steal the underlying technology. Generative AI system attacks - Attacks against AI’s filters and restrictions, intended to generate content deemed harmful or illegal. Supply chain attacks - Attacks against ML artifacts and platforms, with the intention of arbitrary code execution and delivery of traditional malware. Adversarial machine learning attacks - Attacks against AI algorithms, aimed to alter AI’s behavior, evade AI-based detection, or steal the underlying technology. Generative AI system attacks - Attacks against AI’s filters and restrictions, intended to generate content deemed harmful or illegal. Supply chain attacks - Attacks against ML artifacts and platforms, with the intention of arbitrary code execution and delivery of traditional malware. Securing Your AI for Better Data Security Understanding and implementing extensive security measures for AI is no longer a choice. It’s a necessity. Too much is at risk for organizations, government, and society at large. Security must maintain pace with AI to allow innovation to flourish. That is why it is imperative to safeguard your most valuable assets, from development to operation and everything in between. Discovery and Asset Management First, identify where AI is already used in your organization. What applications has your organization already purchased that use AI or have AI-enabled features? Second, evaluate what AI may be under development by your organization. Third, understand what pretrained models from public repositories may already be in use. Risk Assessment and Threat Modelling First, conduct a benefit assessment to identify the potential negative consequences associated with the AI system if those models were to be compromised in any way. Second, perform threat modeling to understand the potential vulnerabilities and attack vectors that could be exploited by malicious actors to complete your understanding of your organization’s AI risk exposure. Data Security and Privacy Go beyond the typical implementation of encryption, access controls, and secure data storage practices to protect your AI model data. Evaluate and implement security solutions that are purpose-built to provide runtime protection for AI models. Model Robustness and Validation Regularly assess the robustness of AI models against adversarial attacks. This involves pen-testing the models’ response to various attacks such as intentionally manipulated inputs. Next, implement model validation techniques to ensure the AI system behaves predictably and reliably in real-world scenarios. This will help minimize the risk of unintended consequences. Continuous Monitoring and Incident Response Implement continuous monitoring mechanisms to detect anomalies and potential security incidents in real time for your AI. Require your vendors to utilize AI in their solutions to alert you to attacks that could compromise your data or business processes. Develop a robust AI incident response plan to quickly and effectively address security breaches or anomalies. Regularly test and update the incident response plan to adapt to evolving AI threats. Conclusion The security landscape as well as AI technology are dynamically and rapidly changing. It’s crucial to stay informed about emerging threats and best practices. Regularly update and refine your AI-specific security program to address new challenges and vulnerabilities. Responsible and ethical AI frameworks in many cases fall short of ensuring models are secure before they go into production, as well as after an AI system is in use. Always ask yourself the following questions 1) What am I doing to secure my organization’s use of AI? 2) Is it enough? 3) How do I know? Only by answering these questions with data-driven, intellectual honesty, can you maintain the integrity of your security role and keep your organization secure.

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