Alpha Nodus

alphanodus

Since the plow, humans have had a natural wariness over technology that seems to threaten their jobs. It’s a natural anxiety. Factories, plows, and automation legitimately have scaled back the need for human labor. And now technology seems to be coming after jobs that previously appeared to be untouchable. Drivers, communications professionals. Even doctors. The past several years have brought developments that seem poised to change things both in the coding and customer communications industries. Are these technologies passing fads or a legitimate threat? In this article, we take a look at what is out there and think about what impact these technologies may have on the job market. Read on to learn more about how AI and ChatGPT may affect , and beyond. careers in the tech industry The Situation In 2021, an innovative AI program was launched. AlphaCode, an AI that could write code and efficiently solve basic problems. Or not so basic, as it would turn out. AlphaCode’s producers, a company by the name of OpenAI began to enter the program into online coding competitions. All of the other competitors in these competitions were human. In contests with 500 people or more, AlphaCode dependably outperformed at least half of the participants. Not only did it perform at a high level, but it dependably wrote new lines of code without needing to rely heavily on duplication  —performing with a level of efficiency and accuracy that surprised even its creators. Of course, in objective terms, outperforming half the people in a contest is not particularly impressive. AlphaCode may have beaten several hundred people, but it lost to several hundred more. Still, the performance invites an alarming question. Will there be a time in the not-so-distant future when AI is good enough to hold a monopoly on coding jobs? Greater Context Coders reading this may notice their muscles tense ever so slightly, but this isn’t necessarily the story of how AI is taking a job that used to be done only by humans. In fact, that was never OpenAI’s intention at all. The company insists that OpenAI was never meant to replace humans completely. “Even if this kind of technology becomes supersuccessful, you would want to treat it the same way you treat a programmer within an organization,” Solar-Lezama, a . “You never want an organization where a single programmer could bring the whole organization down.” developer with the organization says AI is complex. So is coding. Letting a single program shape the way other programs are written could have dire risks. OpenAI views the technology as, at best, a tool to help other programmers work faster and more accurately. The developers also suggest it could be used as a powerful training tool, reverse analyzing existing code to help student programmers understand the purpose of what they are looking at. ChatGPT ChatGPT launched only several months ago as a prototype. Because it’s still very much in its infancy, it is very hard to grasp the full context of its debut as an AI-driven technology. The program is ostensibly a highly sophisticated chatbot that produces articulate responses that are eerily similar to actual human conversation. Early users have reported being extremely impressed by the depth and breadth of the information provided. However, even just several minutes in, there have been many reports that the program suffers significantly from inaccuracies. What Does This Mean for the Tech Industry, and the Job Market at Large? Chatbots have already played a role in helping customer service divisions with their scalability. They have also played a vital role in HR management. However, in both instances there is almost always a human hand at work, guiding the chatbot, and providing additional support where it is needed. Because chatbots are nothing new, it is hard to view ChatGPT as a disruptive technology. Impressive though the program, the mixed results of its launch indicate that it is still a long way off from eliminating customer communications as a human endeavor. ChatGPT could potentially suggest a wider proliferation of chatbot technology. Businesses that haven’t been using chatbots prior to its debut— What businesses are those? I haven’t noticed them. Maybe because you were too busy interrupting to take notice. Businesses that haven’t adopted chatbots as a form of customer communication might be more comfortable doing so if they have the option to use a program that feels more authentically human. This could, of course, have an impact on specific people’s jobs, but it’s hard to anticipate the broader context of what it will mean for communications-based jobs without seeing how the program performs over time. For now, ChatGPY looks more like a tool that will be used with humans than one that will be used to replace them. The Bottom Line Products like ChatGPT, and indeed the larger world of AI hint at a future without people that seem indispensable now. This includes coders, sure, but also writers, customer service professionals, drivers, and many more jobs that have previously required a human touch since the dawn of their existence. And yet it takes only a look at the results that these technologies are producing to understand their limitations. Sure, AI can organize words into sentences on a page. But they can’t produce articles that are as funny, clever, and downright enjoyable as the one in front of you right now. And AI can code, but not at the human level. Not for abstract or creative purposes that define the industry for so many people in the first place. There may be a time when all that changes, but it isn’t now. It’s probably not even soon. Eye your AI with suspicion, sure, but don’t let it keep you up at night. For now, talent and creativity are still bankable skills that you can use to find work in the tech industry, and beyond.

How Coding and Other Tech Careers Could Be Impacted By AI and ChatGPT

The use of Artificial Intelligence (AI) is surging, and one area in which its use is even more important in 2020 – the year of a global pandemic – is in health technology, or healthtech. Berlin-based, non-profit think tank has just released a new report, ”, which looks at the issue of privacy and access to genetic data for companies using AI to speed up and improve drug design. dGen “AI, Privacy, and Genomics: The Next Era of Drug Design With articles about work on a vaccine for COVID-19 flooding newspapers every day, most people are now more aware of the typical timelines involved in creating new drugs. They certainly don’t appear overnight. As the dGen report states, “The average drug today takes 10-12 years and cost $2 billion.” However, the arrival of the new coronavirus has forced researchers to think more in terms of 12-18 months, which is like exchanging a leisurely world cruise for supersonic flight. Enter AI, which in 2020 is only just entering drug R&D where it is being used to test and improve candidate drugs before they can be fully accredited by regulators, such as the FDA in the USA. But there is one area of concern: genetic information is central to many AI-enabled drug discovery startups. To expand this innovation, a number of issues with using genetic data must be resolved. The dGen report lists these as: ownership secure storage availability to multiple research parties. In order for all of us to accept the wider use of AI in drug design, privacy concerns must be addressed using the privacy-preserving techniques in machine learning. These allow researchers to process genetic material without fully revealing its source. While this is crucial for privacy, the techniques do not address the issue of ownership, or ways to audit the system. What the dGen report proposes is a decentralized pan-European biobank network that makes information available to researchers, but all access requests have to be logged. In that way, we all know who has looked at our genetic data. Furthermore, it would allow us as individuals to grant or deny these requests and track the use of our information. dGen’s Top Predictions for 2030 Based on better privacy-preserving technologies and an access network, dGen’s : top predictions for 2030 are Better collaboration networks will emerge Genetic privacy laws will be overhauled AI will become a fundamental part of drug discovery Pharmaceutical giants won’t be toppled, but they won’t get out unscathed as biotech startups take the field The Views of Industry Leaders It is also interesting to note the responses to the dGen report from those working in AI and healthtech. The think tank interviewed industry leaders from Aidence, Gero, Alphanosos, e-Estonia, Qunatlib and Turbine amongst others. Maxim Kholin, Gero Co-Founder said,‘We believe that AI can accelerate the drug discovery process by proper understanding of human diseases from large biomedical data. The data-driven approach should help establish the genetic determinants and molecular markers of the disease’. Pascal Mayer, Founder of Alphanosos, which is specialized in plant-based pharmaceuticals, told dGen: ‘While currently working really well on bacteria, we are confident AI-enabled plant-based drug discovery shall be successful in fighting viruses as well’. This work is important for all of us who have an interest in how emerging technology can contribute to a decentralized future in Europe and what this might mean for people, society, private entities, and the public sector over the coming decades. It is, of course, of a signifiant interest to us all right now, as the search for a Covid-19 cure continues. For a copy of the full report, contact: Francisco Rodríguez: francisco@dgen.org Previously published at https://mehranmuslimiblog.com/2020/08/17/ai-speeds-up-drug-design-as-world-searches-for-covid-19-cure/

Stories, News & Mentions about ALPHANODUS

Alphanodus’s Stories on HackerNoon