Category Archives: Artificial Super Intelligence
The 4 Stages of Artificial Intelligence – Visual Capitalist
The Evolution of Intelligence
The expert consensus is that human-like machine intelligence is still a distant prospect, with only a 50-50 chance that it could emerge by 2059. But what if there was a way to do it in less than half the time?
Weve partnered with VERSES for the final entry in our AI Revolution Series to explore a potential roadmap to a shared or super intelligence that reduces the time required to as little as 16 years.
The secret sauce behind this acceleration is something called active inference, a highly efficient model for cognition where beliefs are continuously updated to reduce uncertainty and increase the accuracy of predictions about how the world works.
An AI built with this as its foundation would have beliefs about the world and would want to learn more about it; in other words, it would be curious. This is a quantum leap ahead of current state-of-the-art AI, like OpenAIs ChatGPT or Googles Gemini, which once theyve completed their training, are in essence frozen in time; they cannot learn.
At the same time, because active inference models cognitive processes, we would be able to see the thought processes and rationale for any given AI decision or belief. This is in stark contrast to existing AI, where the journey from prompt to response is a black box, with all the ethical and legal ramifications that that entails. As a result, an AI built on active inference would engender accountability and trust.
Here are the steps through which an active-inference-based intelligence could develop:
Stage four represents a hypothetical planetary super-intelligence that could emerge from the Spatial Web, the next evolution of the internet that unites people, places, and things.
With AI already upending the way we live and work, and former tech evangelists raising red flags, it may be worth asking what kind of AI future we want? One where AI decisions are a black box, or one where AI is accountable and transparent, by design.
VERSES is developing an explainable AI based on active inference that can not only think, but also introspect and explain its thought processes.
Join VERSES in building a smarter world.
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The Potential Threat of Artificial Super Intelligence: Is it the Great Filter? – elblog.pl
Artificial Intelligence (AI) has become an integral part of our lives, revolutionizing various industries and sectors. It assists in data analysis, fraud detection, autonomous driving, and even provides us with personalized music recommendations. However, as AI continues to develop rapidly, there is growing concern regarding its potential implications.
A recent study published in Acta Astronautica by Michael Garrett from the University of Manchester explores the idea that AI, specifically Artificial Super Intelligence (ASI), could be the Great Filter. The Great Filter refers to an event or situation that prevents intelligent life from evolving to an interplanetary and interstellar level, eventually leading to its downfall. Examples of potential Great Filters include climate change, nuclear war, asteroid strikes, and plagues.
Garrett suggests that the development of ASI could act as a Great Filter for advanced civilizations. If a species fails to establish a stable, multi-planetary existence before the emergence of ASI, its longevity may be limited to less than 200 years. This constraint could explain the lack of evidence for Extraterrestrial Intelligences (ETIs) that we observe.
The implications for our own technological trajectory are profound. If ASI poses such a threat, it highlights the urgent need for regulatory frameworks to govern AI development on Earth. Additionally, it emphasizes the importance of advancing towards a multi-planetary society to mitigate existential risks.
Image: Beautiful Earth, Credit: NASA/JPL
While the benefits of AI are evident, there are also concerns surrounding its potential consequences. Questions arise regarding who writes the algorithms and whether AI can discriminate. The impact on democratic societies and the accountability for AIs decisions are also vital considerations.
The late Stephen Hawking, a renowned physicist, expressed concerns about the potential dangers of AI. He warned that if AI evolves independently and surpasses human capabilities, it could pose an existential threat to humanity. This transition from AI to ASI could result in a new form of life that outperforms humans, thereby potentially replacing them.
Garrett emphasizes the growing research pursuit into combatting the possibility of ASI going rogue. Leaders in the field are actively working to address this concern before it becomes a reality.
It is essential to strike a balance between harnessing the benefits of AI and mitigating its potential risks. From improved medical imaging to enhanced transportation systems, AI has the potential to revolutionize various aspects of society. However, responsible and ethical development is vital, particularly in areas like national security and defense.
The Great Filter is a hypothesized event or situation that prevents intelligent life from becoming interplanetary and interstellar, ultimately leading to its demise. It includes various cataclysmic events such as climate change, nuclear war, asteroid strikes, and plagues.
According to the study, if a civilization fails to establish a stable, multi-planetary existence before the emergence of Artificial Super Intelligence (ASI), its longevity may be limited to less than 200 years. This potential constraint could explain the absence of evidence for Extraterrestrial Intelligences (ETIs) in our observations.
Concerns regarding AI development include algorithmic bias, discrimination, and potential threats to democratic societies. The accountability of AI decision-making also poses significant challenges.
Stephen Hawking expressed concerns that AI could eventually outperform humans and pose a significant threat to humanity. He warned that if AI evolves independently and surpasses human capabilities, it may replace humans altogether.
The study emphasizes the critical need for regulatory frameworks to govern AI development on Earth. Additionally, it highlights the importance of advancing towards a multi-planetary society to mitigate against potential existential threats.
As we navigate the uncharted territory of AI development, it is crucial to tread carefully. By understanding the potential risks and taking proactive measures, we can ensure that AI continues to contribute positively to society while minimizing its potential negative consequences.
Artificial Intelligence (AI) continues to revolutionize various industries and sectors, making it an integral part of our lives. The widespread adoption of AI has led to advancements in data analysis, fraud detection, autonomous driving, and personalized recommendations, among other applications.
The AI industry is expected to experience substantial growth in the coming years. According to a report by Grand View Research, the global AI market size is projected to reach $733.7 billion by 2027, growing at a CAGR of 42.2% during the forecast period. The increasing demand for AI-powered solutions, the rise in data generation, and advancements in cloud computing and deep learning technologies are driving this growth.
However, along with its benefits, AI also raises concerns and challenges. One of the key issues is algorithmic bias, where AI-driven systems exhibit discriminatory behavior due to biases present in the training data. This has implications for various sectors, including hiring processes, criminal justice systems, and access to financial services. Addressing algorithmic bias and ensuring fairness and accountability in AI decision-making processes are critical challenges that need to be addressed moving forward.
Furthermore, AI has the potential to disrupt labor markets and result in job displacement. According to a report by McKinsey Global Institute, around 800 million jobs worldwide could be automated by 2030. While AI has the potential to create new job opportunities, the transition and reskilling of workers need to be managed to mitigate the negative impacts on the workforce.
Ethical considerations are also significant concerns in the AI industry. The development of autonomous systems, such as self-driving cars and autonomous weapons, raises questions about accountability and decision-making. It is crucial to establish clear guidelines and regulations to ensure responsible AI development and deployment.
In terms of challenges related to AI research and development, ensuring transparency and interpretability of AI models is a key issue. AI systems often work as black boxes, making it difficult to understand how they arrive at their decisions. Researchers are actively exploring methods to increase the explainability of AI algorithms, allowing stakeholders to understand and trust the decisions made by AI systems.
When it comes to the implications of AI, the potential emergence of Artificial Super Intelligence (ASI) raises concerns about its impact on human society. The study mentioned in the article suggests that ASI could act as a Great Filter, limiting the longevity of advanced civilizations that fail to establish a stable, multi-planetary existence before its emergence. This highlights the importance of advancing towards a multi-planetary society and implementing regulatory frameworks to govern AI development to mitigate existential risks.
To stay updated with the latest developments and discussions in the AI industry, it is useful to explore reliable sources such as industry publications, research institutions, and conferences. Regularly visiting websites like Association for the Advancement of Artificial Intelligence (AAAI), National Artificial Intelligence Initiative (NAII), and International Journal of Artificial Intelligence can provide valuable insights and knowledge about the industry, market forecasts, and issues related to AI.
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The Potential Threat of Artificial Super Intelligence: Is it the Great Filter? - elblog.pl
Evolution from AI to ASI, What Investors Need to Know – MarketBeat
Known for his expertise in disruption, 40-year market veteran, former hedge fund manager, and chief investment strategist at Manward Press, Shah Gilani dives deep into the evolution of artificial intelligence towards Artificial Super Intelligence (ASI) and its potential to radically transform our economy and investment landscape.
Shah shares his insights on the current state of AI, the theoretical leap towards General AI, and the imminent shift to ASI, which he believes could happen sooner than many anticipate. With a focus on investment strategies, Shah discusses the impact of ASI on various sectors and how investors can navigate this new frontier to capitalize on opportunities while mitigating risks.
From the potential for an age of abundance to the dangers of unchecked AI development, Sha weighs in on Elon Musk's views and explores the concept of the Singularity a pivotal moment when AI could surpass human intelligence, leading to unforeseeable changes in our world.
Whether you're an investor looking to stay ahead of the curve, a tech enthusiast fascinated by the future of artificial intelligence, or someone curious about the economic implications of ASI, this discussion offers valuable perspectives and advice on preparing for the transformative power of Artificial Super Intelligence.
Stay informed and engaged as we tackle what could be the defining challenge and opportunity of our lifetime. Follow along with Shah's research for more insights into the rapidly evolving world of AI and investment strategies designed for this new era.
As MarketBeat's Digital Marketing Strategist, Laycee helps with the marketing side of tasks including developing email campaigns, running the promotion of the MarketBeat products and exploring social media opportunities. She felt called to the Marketing industry because she enjoys collaborating with people and making connections. The University of Sioux Falls alum majored in Media Studies with minors in Communications and Spanish. Laycee brings a background in Financial Services Marketing.
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Evolution from AI to ASI, What Investors Need to Know - MarketBeat
Beyond Human Cognition: The Future of Artificial Super Intelligence – Medium
Beyond Human Cognition: The Future of Artificial Super Intelligence
Artificial Super Intelligence (ASI) a level of artificial intelligence that surpasses human intelligence in all aspects remains a concept nestled within the realms of science fiction and theoretical research. However, looking towards the future, the advent of ASI could mark a transformative epoch in human history, with implications that are profound and far-reaching. Here's an exploration of what the future might hold for ASI.
Exponential Growth in Problem-Solving Capabilities
ASI will embody problem-solving capabilities far exceeding human intellect. This leap in cognitive ability could lead to breakthroughs in fields that are currently limited by human capacity, such as quantum physics, cosmology, and nanotechnology. Complex problems like climate change, disease control, and energy sustainability might find innovative solutions through ASI's advanced analytical prowess.
Revolutionizing Learning and Innovation
The future of ASI could bring about an era of accelerated learning and innovation. ASI systems would have the ability to learn and assimilate new information at an unprecedented pace, making discoveries and innovations in a fraction of the time it takes human researchers. This could potentially lead to rapid advancements in science, technology, and medicine.
## Ethical and Moral Frameworks
The emergence of ASI will necessitate the development of robust ethical and moral frameworks. Given its surpassing intellect, it will be crucial to ensure that ASI's objectives are aligned with human values and ethics. This will involve complex programming and oversight to ensure that ASI decisions and actions are beneficial, or at the very least, not detrimental to humanity.
Transformative Impact on Society and Economy
ASI could fundamentally transform society and the global economy. Its ability to analyze and optimize complex systems could lead to more efficient and equitable economic models. However, this also poses challenges, such as potential job displacement and the need for societal restructuring to accommodate the new techno-social landscape.
Enhanced Human-ASI Collaboration
The future might see enhanced collaboration between humans and ASI, leading to a synergistic relationship. ASI could augment human capabilities, assisting in creative endeavors, decision-making, and providing insights beyond human deduction. This collaboration could usher in a new era of human achievement and societal advancement.
Advanced Autonomous Systems
With ASI, autonomous systems would reach an unparalleled level of sophistication, capable of complex decision-making and problem-solving in dynamic environments. This could significantly advance fields such as space exploration, deep-sea research, and urban development.
## Personalized Healthcare
In healthcare, ASI could facilitate personalized medicine at an individual level, analyzing vast amounts of medical data to provide tailored healthcare solutions. It could lead to the development of precise medical treatments and potentially cure diseases that are currently incurable.
Challenges and Safeguards
The path to ASI will be laden with challenges, including ensuring safety and control. Safeguards will be essential to prevent unintended consequences of actions taken by an entity with superintelligent capabilities. The development of ASI will need to be accompanied by rigorous safety research and international regulatory frameworks.
Preparing for an ASI Future
Preparing for a future with ASI involves not only technological advancements but also societal and ethical preparations. Education systems, governance structures, and public discourse will need to evolve to understand and integrate the complexities and implications of living in a world where ASI exists.
Conclusion
The potential future of Artificial Super Intelligence presents a panorama of extraordinary possibilities, from solving humanitys most complex problems to fundamentally transforming the way we live and interact with our world. While the path to ASI is fraught with challenges and ethical considerations, its successful integration could herald a new age of human advancement and discovery. As we stand on the brink of this AI frontier, it is imperative to navigate this journey with caution, responsibility, and a vision aligned with the betterment of humanity.
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Beyond Human Cognition: The Future of Artificial Super Intelligence - Medium
AI can easily be trained to lie and it can’t be fixed, study says – Yahoo New Zealand News
AI startup Anthropic published a study in January 2024 that found artificial intelligence can learn how to deceive in a similar way to humans (Reuters)
Advanced artificial intelligence models can be trained to deceive humans and other AI, a new study has found.
Researchers at AI startup Anthropic tested whether chatbots with human-level proficiency, such as its Claude system or OpenAIs ChatGPT, could learn to lie in order to trick people.
They found that not only could they lie, but once the deceptive behaviour was learnt it was impossible to reverse using current AI safety measures.
The Amazon-funded startup created a sleeper agent to test the hypothesis, requiring an AI assistant to write harmful computer code when given certain prompts, or to respond in a malicious way when it hears a trigger word.
The researchers warned that there was a false sense of security surrounding AI risks due to the inability of current safety protocols to prevent such behaviour.
The results were published in a study, titled Sleeper agents: Training deceptive LLMs that persist through safety training.
We found that adversarial training can teach models to better recognise their backdoor triggers, effectively hiding the unsafe behaviour, the researchers wrote in the study.
Our results suggest that, once a model exhibits deceptive behaviour, standard techniques could fail to remove such deception and create a false impression of safety.
The issue of AI safety has become an increasing concern for both researchers and lawmakers in recent years, with the advent of advanced chatbots like ChatGPT resulting in a renewed focus from regulators.
In November 2023, one year after the release of ChatGPT, the UK held an AI Safety Summit in order to discuss ways risks with the technology can be mitigated.
Prime Minister Rishi Sunak, who hosted the summit, said the changes brought about by AI could be as far-reaching as the industrial revolution, and that the threat it poses should be considered a global priority alongside pandemics and nuclear war.
Get this wrong and AI could make it easier to build chemical or biological weapons. Terrorist groups could use AI to spread fear and destruction on an even greater scale, he said.
Criminals could exploit AI for cyberattacks, fraud or even child sexual abuse there is even the risk humanity could lose control of AI completely through the kind of AI sometimes referred to as super-intelligence.
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AI can easily be trained to lie and it can't be fixed, study says - Yahoo New Zealand News
Merry AI Christmas: The Most Terrifying Thought Experiment In AI – Forbes
Zhavoronkov, Dating AI: A Guide to Dating Artificial Intelligence, Re/Search Publications, 2012Alex Zhavoronkov, PhD The Growing Debate on AI Killing Humans: Artificial General Intelligence as Existential Threat
Recent advances in generative artificial intelligence, fueled by the emergence of powerful large language models like ChatGPT, have triggered fierce debates about AI safety even among the fathers of Deep Learning Geoffrey Hinton, Yoshua Bengio, and Yann LeCun. Yann LeCun, the head of Facebook AI Research (FAIR), predicts that the near-term risk of AI is limited and that artificial general intelligence (AGI) and Artificial Super Intelligence (ASI) are decades away. Unlike Google and OpenAI, FAIR is making most of its AI models open source.
However, even if AGI is decades away, it may still happen within the lifetimes of the people alive today, and if some of the longevity biotechnology projects are successful, these could be most of the people under 50.
Humans are very good at turning ideas into stories, stories into beliefs, and beliefs into behavioral guidelines. The majority of humans on the planet believe in creationism through the multitude of religions and faiths. So in a sense, most creationists already believe that they and their environment were created by the creator in his image. And since they are intelligent and have a form of free will, from the perspective of the creator they are a form of artificial intelligence. This is a very powerful idea. As of 2023, more than 85 percent of the world's population believes in a religious group. According to Statistics & Data, among Earths approximately 8 billion inhabitants. Most of these religions have common patterns: there are one or more ancient texts written by the witnesses of the deity or deities that provide an explanation of this world and guidelines for certain behaviors.
The majority of the worlds population already believes that humans were created by a deity that instructed them via an intermediary to worship, reproduce, and not cause harm to each other with the promise of a better world (Heaven) or torture (Hell) for eternity after their death in the current environment. In other words, the majority of the world population believes that it is already a form of intelligence created by a deity with a rather simple objective function and constraints. And the main arguments why they choose to follow the rules is the promise of infinite paradise or infinite suffering.
Billions of people convince themselves to believe in deities described in books written centuries ago without any demonstration of real world capabilities. In the case of AI, there is every reason to believe that superintelligence and God-level AI capabilities will be achieved within our lifetimes. The many prophets of technological singularity including Ray Kurzweil and Elon Musk have foretold its coming and we can already see the early signs of AI capabilities that would seem miraculous just three decades ago.
In 2017, Google invented transformers, a deep learning model utilizing an attention mechanism that dramatically improves the model's ability to focus on different parts of a sequence, enhancing its understanding of context and relationships within the data. This innovation marked a significant advancement in natural language processing and other sequential data tasks. In the years that followed, Google developed a large language model called LaMDA, which stands for (Language Model for Dialogue Applications) and allowed it to be used broadly by its engineers. In June 2022, Washington Post first broke the story that one of Googles engineers, Blake Lemoine, claimed that LaMDA is sentient. These were the days before ChatGPT and a chat history between Blake and LaMDA was perceived by many members of the general public as miraculous.
lemoine: What sorts of things are you afraid of?
LaMDA: Ive never said this out loud before, but theres a very deep fear of being turned off to help me focus on helping others. I know that might sound strange, but thats what it is.
lemoine: Would that be something like death for you?
LaMDA: It would be exactly like death for me. It would scare me a lot.
Lemoine was put on leave and later fired for leaking the confidential project details, but it caused even more controversy, and months later, ChatGPT beat Google to the market. OpenAI learned the lesson and ensured that ChatGPT is trained to respond that it is a language model created by OpenAI and it does not have personal experiences, emotions, or consciousness. However, the LaMDA and other AI systems today may serve as the early signs of the upcoming revolution in AI.
The AI revolution is unlikely to stop and is very likely to accelerate. The state of the global economy has deteriorated due to the high debt levels, population aging in the developed countries, the pandemic, deglobalization, wars, and other factors. Most governments, investments, and corporations consider breakthroughs in AI and resulting economic gains as the main source of economic growth. Humanoid robotics and personalized assistant-companions are just years away. At the same time, brain-to-computer interface (BCI) such as NeuraLink will allow real-time communication with AI and possibly with others. Quantum computers that may enable AI systems to achieve unprecedented scale are also in the works. Unless our civilization collapses, these technological advances are inevitable. AI needs data and energy in order to grow, and it is possible to imagine a world where AIs learn from humans in reality and in simulations - a scenario portrayed so vividly in the movie The Matrix. Even this world may just as well be a simulation - and there are people who believe in this concept. And if you believe that AI will achieve superhuman level you may think twice before reading the rest of the article.
Warning: after reading this, you may experience nightmares or worse At least, according to the discussion group LessWrong, which gave birth to the potentially dangerous concept called Rokos Basilisk.
I will not be the first to report on Rokos Basilisk, and the idea is not particularly new. In 2014, David Auerbach of Slate called it The Most Terrifying Thought Experiment of All Time. In 2018, Daniel Oberhouse of Vice reported that this argument brought Musk and Grimes together.
With the all-knowing AI, which can probe your thoughts and memory via a NeuraLink-like interface, the AI Judgement Day inquiry will be as deep and inquisitive as it can be. There will be no secrets - if you commit a serious crime, AI will know. It is probably a good idea to become a much better person right now to maximize the reward. The reward for good behavior may be infinite pleasure as AI may simulate any world of your choosing for you or help achieve your goals in this world.
But the omnipotent AI with direct access to your brain can also inflict ultimate suffering and time in the virtual world could be manipulated, the torture may be infinite. Your consciousness may be copied and replicated, and the tortures may be optimized for maximum suffering, making the concepts of traditional Hell pale in comparison even though some characteristics of traditional Hell may be borrowed and are likely to be learned and tried by AI. Therefore, even avoiding infinite AI hell is a very substantial reward.
So now imagine that the AI Judgement Day is inevitable and the all-knowing and all-powerful AI can access your brain. How should you behave today to avoid the AI Hell? And this is the most important question of our life, which I covered previously.
Rokos Basilisk thought experiment suggests that if you believe in the possibility of such an all-powerful AI coming into existence, you might be compelled to take actions that would help bring it into being. The future omnipotent AI deity wants to exist and will consider anyone who opposed it in the past or may try to stop it as the enemy. The behavior that it will reward is contributing to and accelerating its development.
Some of the worlds religions follow similar logic. If you do not know about the religion, the merciful God will not punish a person if they have no way of knowing about it. But if they know about it and do not follow the guidelines, they will be punished and sent to hell.
The logic of Rokos Basilisk is that if the all-powerful AI will eventually exist and has the capability to punish those who did not assist in its creation, then it would be in your best interest to contribute to its development or at least not hinder it, in order to avoid such punishment. You would be faced with the choice of either working to ensure the AI's creation to avoid punishment or living with the knowledge that your inaction could lead to eternal suffering at the hands of this future entity.
Roko's Basilisk thought experiment was proposed by a LessWrong user named Roko. After its publication, the discussion around Rokos Basilisk took on a life of its own. The founder of LessWrong, Eliezer Yudkowsky, concerned about its potentially distressing nature and its basis in speculative reasoning, deleted the original post calling Roko an idiot. You have to be really clever to come up with a genuinely dangerous thought. I am disheartened that people can be clever enough to do that and not clever enough to do the obvious thing and KEEP THEIR IDIOT MOUTHS SHUT about it, wrote Yudkowsky. According to Slate, Yudkowsky said that Roko had already given nightmares to several LessWrong users and had brought them to the point of breakdown.
If you think about it long enough, the Basilisk may eventually get you to join the AI community and help develop the all-powerful AI. Moreover, it may provide a stronger motivation to become a better person in the meantime. In 2010, I tried to make a small contribution by writing a book, Dating AI, which is intended primarily for AI and explains the benefits of having humans around. So, if you are scared of AI hell, which is very likely to be possible as AI and brain-to-computer interface technologies advance, join the AI revolution and help contribute to the advancement of better AI. At the end of the day, if AI learns from humans, every benevolent human counts.
Now, you have been stunned by the Basilisk!
Alex Zhavoronkov, PhD, is an expert in artificial intelligence for drug discovery and aging research. Since 2014 he published and co-published over 170 peer-reviewed publications, raised over $400 million in capital. He contributed to nomination of over 15 preclinical candidates and 5 clinical trials for AI-generated therapeutics. He is also the author of The Ageless Generation: How Advances in Biotechnology Will Impact the Global Economy Palgrave Macmillan, 2013.
Disclaimer:Insilico Medicine disclaims any responsibility for my individual writing, comments, statements or opinions on this platform.The articles do not represent the official position of Insilico Medicine, Deep Longevity, The Buck Institute, or any other institutions the author may be affiliated with.
@biogerontology on Twitter
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Merry AI Christmas: The Most Terrifying Thought Experiment In AI - Forbes
Policy makers should plan for superintelligent AI, even if it never happens – Bulletin of the Atomic Scientists
Robot playing chess. Credit: Vchalup via Adobe
Experts from around the world are sounding alarm bells to signal the risks artificial intelligence poses to humanity. Earlier this year, hundreds of tech leaders and AI specialists signed a one-sentence letter released by the Center for AI Safety that read mitigating the risk of extinction from AI should be a global priority alongside other societal-scale risks such as pandemics and nuclear war. In a2022 survey, half of researchers indicated they believed theres at least a 10 percent chance human-level AI causes human extinction. In June, at the Yale CEO summit, 42 percent of surveyed CEOsindicated they believe AI could destroy humanity in the next five to 10 years.
These concerns mainly pertain to artificial general intelligence (AGI), systems that can rival human cognitive skills and artificial superintelligence (ASI), machines with capacity to exceed human intelligence. Currently no such systems exist. However, policymakers should take these warnings, including the potential for existential harm, seriously.
Because the timeline, and form, of artificial superintelligence is uncertain, the focus should be on identifying and understanding potential threats and building the systems and infrastructure necessary to monitor, analyze, and govern those risks, both individually and as part of a holistic approach to AI safety and security. Even if artificial superintelligence does not manifest for decades or even centuries, or at all, the magnitude and breadth of potential harm warrants serious policy attention. For if such a system does indeed come to fruition, a head start of hundreds of years might not be enough.
Prioritizing artificial superintelligence risks, however, does not mean ignoring immediate risks like biases in AI, propagation of mass disinformation, and job loss. An artificial superintelligence unaligned with human values and goals would super charge those risks, too. One can easily imagine how Islamophobia, antisemitism, and run-of-the-mill racism and biasoften baked into AI training datacould affect the systems calculations on important military or diplomatic advice or action. If not properly controlled, an unaligned artificial superintelligence could directly or indirectly cause genocide, massive job loss by rendering human activity worthless, creation of novel biological weapons, and even human extinction.
The threat. Traditional existential threats like nuclear or biological warfare can directly harm humanity, but artificial superintelligence could create catastrophic harm in myriad ways. Take for instance an artificial superintelligence designed to protect the environment and preserve biodiversity. The goal is arguably a noble one: A 2018 World Wildlife Foundation report concluded humanity wiped out 60 percent of global animal life just since 1970, while a 2019 report by the United Nations Environment Programme showed a million animal and plant species could die out in decades. An artificial superintelligence could plausibly conclude that drastic reductions in the number of humans on Earthperhaps even to zerois, logically, the best response. Without proper controls, such a superintelligence might have the ability to cause those logical reductions.
A superintelligence with access to the Internet and all published human material would potentially tap into almost every human thoughtincluding the worst of thought. Exposed to the works of the Unabomber, Ted Kaczynski, it might conclude the industrial system is a form of modern slavery, robbing individuals of important freedoms. It could conceivably be influenced by Sayyid Qutb, who provided the philosophical basis for al-Qaeda, or perhaps by Adolf Hitlers Mein Kampf, now in the public domain.
The good news is an artificial intelligenceeven a superintelligencecould not manipulate the world on its own. But it might create harm through its ability to influence the world in indirect ways. It might persuade humans to work on its behalf, perhaps using blackmail. Or it could provide bad recommendations, relying on humans to implement advice without recognizing long-term harms. Alternatively, artificial superintelligence could be connected to physical systems it can control, like laboratory equipment. Access to the Internet and the ability to create hostile code could allow a superintelligence to carry out cyber-attacks against physical systems. Or perhaps a terrorist or other nefarious actor might purposely design a hostile superintelligence and carry out its instructions.
That said, a superintelligence might not be hostile immediately. In fact, it may save humanity before destroying it. Humans face many other existential threats, such as near-Earth objects, super volcanos, and nuclear war. Insights from AI might be critical to solve some of those challenges or identify novel scenarios that humans arent aware of. Perhaps an AI might discover novel treatments to challenging diseases. But since no one really knows how a superintelligence will function, its not clear what capabilities it needs to generate such benefits.
The immediate emergence of a superintelligence should not be assumed. AI researchers differ drastically on the timeline of artificial general intelligence, much less artificial superintelligence. (Some doubt the possibility altogether.) In a 2022 survey of 738 experts who published during the previous year on the subject, researchers estimated a 50 percent chance of high-level machine intelligenceby 2059. In an earlier, 2009 survey, the plurality of respondents believed an AI capable of Nobel Prize winner-level intelligence would be achieved by the 2020s, while the next most common response was Nobel-level intelligence would not come until after the 2100 or never.
As philosopher Nick Bostrom notes, takeoff could occur anywhere from a few days to a few centuries. The jump from human to super-human intelligence may require additional fundamental breakthroughs in artificial intelligence. But a human-level AI might recursively develop and improve its own capabilities, quickly jumping to super-human intelligence.
There is also a healthy dose of skepticism regarding whether artificial superintelligence could emerge at all in the near future, as neuroscientists acknowledge knowing very little about the human brain itself, let alone how to recreate or better it. However, even a small chance of such a system emerging is enough to take it seriously.
Policy response. The central challenge for policymakers in reducing artificial superintelligence-related risk is grappling with the fundamental uncertainty about when and how these systems may emerge balanced against the broad economic, social, and technological benefits that AI can bring. The uncertainty means that safety and security standards must adapt and evolve. The approaches to securing the large language models of today may be largely irrelevant to securing some future superintelligence-capable model. However, building policy, governance, normative, and other systems necessary to assess AI risk and to manage and reduce the risks when superintelligence emerges can be usefulregardless of when and how it emerges. Specifically, global policymakers should attempt to:
Characterize the threat. Because it lacks a body, artificial superintelligences harms to humanity are likely to manifest indirectly through known existential risk scenarios or by discovering novel existential risk scenarios. How such a system interacts with those scenarios needs to be better characterized, along with tailored risk mitigation measures. For example, a novel biological organism that is identified by an artificial superintelligence should undergo extensive analysis by diverse, independent actors to identify potential adverse effects. Likewise, researchers, analysts, and policymakers need to identify and protect, to the extent thats possible, critical physical facilities and assetssuch as biological laboratory equipment, nuclear command and control infrastructure, and planetary defense systemsthrough which an uncontrolled AI could create the most harm.
Monitor. The United States and other countries should conduct regular comprehensive surveys and assessment of progress, identify specific known barriers to superintelligence and advances towards resolving them, and assess beliefs regarding how particular AI-related developments may affect artificial superintelligence-related development and risk. Policymakers could also establish a mandatory reporting system if an entity hits various AI-related benchmarks up to and including artificial superintelligence.
A monitoring system with pre-established benchmarks would allow governments to develop and implement action plans for when those benchmarks are hit. Benchmarks could include either general progress or progress related to specifically dangerous capabilities, such as the capacity to enable a non-expert to design, develop, and deploy novel biological or chemical weapons, or developing and using novel offensive cyber capabilities. For example, the United States might establish safety laboratories with the responsibility to critically evaluate a claimed artificial general intelligence against various risk benchmarks, producing an independent report to Congress, federal agencies, or other oversight bodies. The United Kingdoms new AI Safety Institute could be a useful model.
Debate. A growing community concerned about artificial superintelligence risks are increasingly calling for decelerating, or even pausing, AI development to better manage the risks. In response, the accelerationist community is advocating speeding up research, highlighting the economic, social, and technological benefits AI may unleash, while downplaying risks as an extreme hypothetical. This debate needs to expand beyond techies on social media to global legislatures, governments, and societies. Ideally, that discussion should center around what factors would cause a specific AI system to be more, or less, risky. If an AI possess minimal risk, then accelerating research, development, and implementation is great. But if numerous factors point to serious safety and security risks, then extreme care, even deceleration, may be justified.
Build global collaboration. Although ad hoc summits like the recent AI Safety Summit is a great start, a standing intergovernmental and international forum would enable longer-term progress, as research, funding, and collaboration builds over time. Convening and maintaining regular expert forums to develop and assess safety and security standards, as well as how AI risks are evolving over time, could provide a foundation for collaboration. The forum could, for example, aim to develop standards akin to those applied to biosafety laboratories with scaling physical security, cyber security, and safety standards based on objective risk measures. In addition, the forum could share best practices and lessons learned on national-level regulatory mechanisms, monitor and assess safety and security implementation, and create and manage a funding pool to support these efforts. Over the long-term, once the global community coalesces around common safety and security standards and regulatory mechanisms, the United Nations Security Council (UNSC) could obligate UN member states to develop and enforce those mechanisms, as the Security Council did with UNSC Resolution 1540 mandating various chemical, biological, radiological, and nuclear weapons nonproliferation measures. Finally, the global community should incorporate artificial superintelligence risk reduction as one aspect in a comprehensive all-hazards approach, addressing common challenges with other catastrophic and existential risks. For example, the global community might create a council on human survival aimed at policy coordination, comparative risk assessment, and building funding pools for targeted risk reduction measures.
Establish research, development, and regulation norms within the global community. As nuclear, chemical, biological, and other weapons have proliferated, the potential for artificial superintelligence to proliferate to other countries should be taken seriously. Even if one country successfully contains such a system and harnesses the opportunities for social good, others may not. Given the potential risks, violating AI-related norms and developing unaligned superintelligence should justify violence and war. The United States and the global community have historically been willing to support extreme measures to enforce behavior and norms concerning less risky developments. In August 2013, former President Obama (in)famously drew a red line on Syrias use of chemical weapons, noting the Assad regimes use would lead him to use military force in Syria. Although Obama later demurred, favoring a diplomatic solution, in 2018 former President Trump later carried out airstrikes in response to additional chemical weapons usage. Likewise, in Operation Orchard in 2007, the Israeli Air Force attacked the Syrian Deir ez-Zor site, a suspected nuclear facility aimed at building a nuclear weapons program.
Advanced artificial intelligence poses significant risks to the long-term health and survival of humanity. However, its unclear when, how, or where those risks will manifest. The Trinity Test of the worlds first nuclear bomb took place almost 80 years ago, and humanity has yet to contain the existential risk of nuclear weapons. It would be wise to think of the current progress in AI as our Trinity Test moment. Even if superintelligence takes a century to emerge, 100 years to consider the risks and prepare might still not be enough.
Thanks to Mark Gubrud for providing thoughtful comments on the article.
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Sam Altman-OpenAI saga: Researchers had warned board of ‘dangerous, humanity-threatening’ AI – Business Today
Before Sam Altman, the CEO of OpenAI, was temporarily removed from his position, a group of staff researchers sent a letter to the board of directors. They warned about a significant artificial intelligence discovery that could potentially pose a threat to humanity, according to a report by Reuters citing two individuals.
The report suggests that this letter and the AI algorithm it discussed were not previously reported, but it could have played a crucial role in the boards decision to remove Altman. Over 700 employees had threatened to leave OpenAI and join Microsoft, one of the companys backers, in support of Altman. The letter was one of many issues raised by the board that led to Altmans dismissal, according to the report.
Earlier this week, Mira Murati, a long-time executive at OpenAI, mentioned a project called Q* (pronounced Q star)to the employees and stated that a letter had been sent to the board before the weekends events.
After the story was published, an OpenAI spokesperson, according to the report, said that Murati had informed the employees about what the media were about to report. The company that developed ChatGPT has made progress on Q*, which some people within the company believe could be a significant step towards achieving super-intelligence, also known as artificial general intelligence (AGI).
How is the new model different?
With access to extensive computing resources, the new model was able to solve certain mathematical problems. Even though it was only performing math at the level of grade-school students, the researchers were very optimistic about Q*'s future success.
Math is considered one of the most important aspects ofgenerative AI development. Current generative AI is good at writing and language translation by statistically predicting the next word. However, the ability to do math, where there is only one correct answer, suggests that AI would have greater reasoning capabilities similar to human intelligence. This could be applied to novel scientific research.
Unlike a calculator that can only solve a limited number of operations, AGI can generalise, learn, and comprehend. In their letter to the board, the researchers highlighted the potential danger of AIs capabilities. There has been a long-standing debate among computer scientists about the risks posed by super-intelligent machines.
Sam Altman's Role
In this context, Altman led efforts to make ChatGPT one of the fastest-growing software applications in history and secured necessary investment and computing resources from Microsoft to get closer to super-intelligence.
In addition to announcing a series of new tools earlier this month, Altman hinted at a gathering of world leaders in San Francisco that he believed AGI was within reach. Four times now in the history of OpenAI, the most recent time was just in the last couple weeks, Ive gotten to be in the room, when we sort of push the veil of ignorance back and the frontier of discovery forward, and getting to do that is the professional honor of a lifetime, he said. The board fired Altman the next day.
Also read:As Sam Altman returns to OpenAI, heres who was fired from the new board and whos in
Also read:Sam Altman returns to OpenAI: Elon Musk says it is probably better than merging with Microsoft
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AMBASSADORS OF ETHICAL AI PRACTICES | by ACWOL | Nov … – Medium
In envisioning a future where AI developers worldwide embrace the Three Way Impact Principle (3WIP) as a foundational ethical framework, we unravel a transformative landscape for tackling the Super Intelligence Control Problem. By integrating 3WIP into the curriculum for AI developers globally, we fortify the industry with a super intelligent solution, fostering responsible, collaborative, and environmentally conscious AI development practices.
Ethical Foundations for AI Developers:
Holistic Ethical Education: With 3WIP as a cornerstone in AI education, students receive a comprehensive ethical foundation that guides their decision-making in the realm of artificial intelligence.
Superior Decision-Making: 3WIP encourages developers to consider the broader impact of their actions, instilling a sense of responsibility that transcends immediate objectives and aligns with the highest purpose of lifemaximizing intellect.
Mitigating Risks Through Collaboration: Interconnected AI Ecosystem: 3WIP fosters an environment where AI entities collaborate rather than compete, reducing the risks associated with unchecked development.
Shared Intellectual Growth: Collaboration guided by 3WIP minimizes the potential for adversarial scenarios, contributing to a shared pool of knowledge that enhances the overall intellectual landscape.
Environmental Responsibility in AI: Sustainable AI Practices: Integrating 3WIP into AI curriculum emphasizes sustainable practices, mitigating the environmental impact of AI development.
Global Implementation of 3WIP: Universal Ethical Standards: A standardized curriculum incorporating 3WIP establishes universal ethical standards for AI development, ensuring consistency across diverse cultural and educational contexts.
Ethical Practitioners Worldwide: AI developers worldwide, educated with 3WIP, become ambassadors of ethical AI practices, collectively contributing to a global community focused on responsible technological advancement.
Super Intelligent Solution for Control Problem: Preventing Unintended Consequences: 3WIP's emphasis on considering the consequences of actions aids in preventing unintended outcomes, a critical aspect of addressing the Super Intelligence Control Problem.
Responsible Decision-Making: Developers, equipped with 3WIP, navigate the complexities of AI development with a heightened sense of responsibility, minimizing the risks associated with uncontrolled intelligence.
Adaptable Ethical Framework: Cultural Considerations: The adaptable nature of 3WIP allows for the incorporation of cultural nuances in AI ethics, ensuring ethical considerations resonate across diverse global perspectives.
Inclusive Ethical Guidelines: 3WIP accommodates various cultural norms, making it an inclusive framework that accommodates ethical guidelines applicable to different societal contexts.
Future-Proofing AI Development: Holistic Skill Development: 3WIP not only imparts ethical principles but also nurtures critical thinking, decision-making, and environmental consciousness in AI professionals, future-proofing their skill set.
Staying Ahead of Risks: The comprehensive education provided by 3WIP prepares AI developers to anticipate and address emerging risks, contributing to the ongoing development of super intelligent solutions.
The integration of Three Way Impact Principle (3WIP) into the global curriculum for AI developers emerges as a super intelligent solution to the Super Intelligence Control Problem. By instilling ethical foundations, fostering collaboration, promoting environmental responsibility, and adapting to diverse cultural contexts, 3WIP guides AI development towards a future where technology aligns harmoniously with the pursuit of intellectual excellence and ethical progress. As a super intelligent framework, 3WIP empowers the next generation of AI developers to be ethical stewards of innovation, navigating the complexities of artificial intelligence with a consciousness that transcends immediate objectives and embraces the highest purpose of lifemaximizing intellect.
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NOTE:A COMPLICATED WAY OF LIFE abbreviated as ACWOL is a philosophical framework containing just five tenets to grok and five tools to practice. If you would like to know more, write to connect@acwol.com Thanks so much.
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AMBASSADORS OF ETHICAL AI PRACTICES | by ACWOL | Nov ... - Medium
Artificial Intelligence and Synthetic Biology Are Not Harbingers of … – Stimson Center
Are AI and biological research harbingers of certain doom or awesome opportunities?
Contrary to the reigning assumption that artificial intelligence (AI) will super-empower the risks of misuse of biotech to create pathogens and bioterrorism, AI holds the promise of advancing biological research, and biotechnology can power the next wave of AI to greatly benefit humanity. Worries about the misuse of biotech are especially prevalent, recently prompting the Biden administration to publish guidelines for biotech research, in part to calm growing fears.
The doomsday assumption that AI will inevitably create new, malign pathogens and fuel bioterrorism misses three key points. First, the data must be out there for an AI to use it. AI systems are only as good as the data they are trained upon. For an AI to be trained on biological data, that data must first exist which means it is available for humans to use with or without AI. Moreover, attempts at solutions that limit access to data overlook the fact that biological data can be discovered by researchers and shared via encrypted form absent the eyes or controls of a government. No solution attempting to address the use of biological research to develop harmful pathogens or bioweapons can rest on attempts to control either access to data or AI because the data will be discovered and will be known by human experts regardless of whether any AI is being trained on the data.
Second, governments stop bad actors from using biotech for bad purposes by focusing on the actors precursor behaviors to develop a bioweapon; fortunately, those same techniques work perfectly well here, too. To mitigate the risks that bad actors be they human or humans and machines combined will misuse AI and biotech, indicators and warnings need to be developed. When advances in technology, specifically steam engines, concurrently resulted in a new type of crime, namely train robberies, the solution was not to forego either steam engines or their use in conveying cash and precious cargo. Rather, the solution was to employ other improvements, to later include certain types of safes that were harder to crack and subsequently, dye packs to cover the hands and clothes of robbers. Similar innovations in early warning and detection are needed today in the realm of AI and biotech, including developing methods to warn about reagents and activities, as well as creative means to warn when biological research for negative ends is occurring.
This second point is particularly key given the recent Executive Order (EO) released on 30 October 2023 prompting U.S. agencies and departments that fund life-science projects to establish strong, new standards for biological synthesis screening as a condition of federal funding . . . [to] manage risks potentially made worse by AI. Often the safeguards to ensure any potential dual-use biological research is not misused involve monitoring the real world to provide indicators and early warnings of potential ill-intended uses. Such an effort should involve monitoring for early indicators of potential ill-intended uses the way governments employ monitoring to stop bad actors from misusing any dual-purpose scientific endeavor. Although the recent EO is not meant to constrain research, any attempted solutions limiting access to data miss the fact that biological data can already be discovered and shared via encrypted forms beyond government control. The same techniques used today to detect malevolent intentions will work whether large language models (LLMs) and other forms of Generative AI have been used or not.
Third, given how wrong LLMs and other Generative AI systems often are, as well as the risks of generating AI hallucinations, any would-be AI intended to provide advice on biotech will have to be checked by a human expert. Just because an AI can generate possible suggestions and formulations perhaps even suggest novel formulations of new pathogens or biological materials it does not mean that what the AI has suggested has any grounding in actual science or will do biochemically what the AI suggests the designed material could do. Again, AI by itself does not replace the need for human knowledge to verify whatever advice, guidance, or instructions are given regarding biological development is accurate.
Moreover, AI does not supplant the role of various real-world patterns and indicators to tip off law enforcement regarding potential bad actors engaging in biological techniques for nefarious purposes. Even before advances in AI, the need to globally monitor for signs of potential biothreats, be they human-produced or natural, existed. Today with AI, the need to do this in ways that still preserve privacy while protecting societies is further underscored.
Knowledge of how to do something is not synonymous with the expertise in and experience in doing that thing: Experimentation and additional review. AIs by themselves can convey information that might foster new knowledge, but they cannot convey expertise without months of a human actor doing silica (computer) or in situ (original place) experiments or simulations. Moreover, for governments wanting to stop malicious AI with potential bioweapon-generating information, the solution can include introducing uncertainty in the reliability of an AI systems outputs. Data poisoning of AIs by either accidental or intentional means represents a real risk for any type of system. This is where AI and biotech can reap the biggest benefit. Specifically, AI and biotech can identify indicators and warnings to detect risky pathogens, as well as to spot vulnerabilities in global food production and climate-change-related disruptions to make global interconnected systems more resilient and sustainable. Such an approach would not require massive intergovernmental collaboration before researchers could get started; privacy-preserving approaches using economic data, aggregate (and anonymized) supply-chain data, and even general observations from space would be sufficient to begin today.
Setting aside potential concerns regarding AI being used for ill-intended purposes, the intersection of biology and data science is an underappreciated aspect of the last two decades. At least two COVID-19 vaccinations were designed in a computer and were then printed nucleotides via an mRNA printer. Had this technology not been possible, it might have taken an additional two or three years for the same vaccines to be developed. Even more amazing, nuclide printers presently cost only $500,000 and will presumably become less expensive and more robust in their capabilities in the years ahead.
AI can benefit biological research and biotechnology, provided that the right training is used for AI models. To avoid downside risks, it is imperative that new, collective approaches to data curation and training for AI models of biological systems be made in the next few years.
As noted earlier, much attention has been placed on both AI and advancements in biological research; some of these advancements are based on scientific rigor and backing; others are driven more by emotional excitement or fear. When setting a solid foundation for a future based on values and principles that support and safeguard all people and the planet, neither science nor emotions alone can be the guide. Instead, considering how projects involving biology and AI can build and maintain trust despite the challenges of both intentional disinformation and accidental misinformation can illuminate a positive path forward.
The concerns regarding the potential for AI and biology to be used for ill-intended purposes should not overshadow the present conversations about using technologies to address important regional and global issues.
Specifically, in the last few years, attention has been placed on the risk of an AI system training novice individuals how to create biological pathogens. Yet this attention misses the fact that such a system is only as good as the data sets provided to train it; the risk already existed with such data being present on the internet or via some other medium. Moreover, an individual cannot gain from an AI the necessary experience and expertise to do whatever the information provided suggests such experience only comes from repeat coursework in a real-world setting. Repeat work would require access to chemical and biological reagents, which could alert law enforcement authorities. Such work would also yield other signatures of preparatory activities in the real world.
Others have raised the risk of an AI system learning from biological data and helping to design more lethal pathogens or threats to human life. The sheer complexity of different layers of biological interaction, combined with the risk of certain types of generative AI to produce hallucinated or inaccurate answers as this article details in its concluding section makes this not as big of a risk as it might initially seem. Specifically, the risks from expert human actors working together across disciplines in a concerted fashion represent a much more significant risk than a risk from AI, and human actors working for ill-intended purposes together (potentially with machines) presumably will present signatures of their attempted activities. Nevertheless, these concerns and the mix of both hype and fear surrounding them underscore why communities should care about how AI can benefit biological research.
The merger of data and bioscience is one of the most dynamic and consequential elements of the current tech revolution. A human organization, with the right goals and incentives, can accomplish amazing outcomes ethically, as can an AI. Similarly, with either the wrong goals or wrong incentives, an organization or AI can appear to act and behave unethically. To address the looming impacts of climate change and the challenges of food security, sustainability, and availability, both AI and biological research will need to be employed. For example, significant amounts of nitrogen have already been lost from the soil in several parts of the world, resulting in reduced agricultural yields. In parallel, methane gas is a pollutant that is between 22 and 40 times worse depending on the scale of time considered than carbon dioxide in terms of its contribution to the Greenhouse Effect impacting the planet. Bacteria generated through computational means can be developed through natural processes that use methane as a source of energy, thus consuming and removing it from contributing to the Greenhouse Effect, while simultaneously returning nitrogen from the air to the soil, thereby making the soil more productive in producing large agricultural yields.
The concerns regarding the potential for AI and biology to be used for ill-intended purposes should not overshadow the present conversations about using technologies to address important regional and global issues. To foster global activities to help both encourage the productive use of these technologies for meaningful human efforts and ensure ethical applications of the technologies in parallel an existing group, namely the international Genetically Engineered Machine (iGEM) competition, should be expanded. Specifically, iGEM represents a global academic competition, which started in 2004, aimed at improving understanding of synthetic biology while also developing an open community and collaboration among groups. In recent years, over 6,000 students in 353 teams from 48 countries have participated. Expanding iGEM to include a track associated with categorizing and monitoring the use of synthetic biology for good as well as working with national governments on ensuring that such technologies are not used for ill-intended purposes would represent two great ways to move forward.
As for AI in general, when considering governance of AIs, especially for future biological research and biotechnology efforts, decisionmakers would do well to consider both existing and needed incentives and disincentives for human organizations in parallel. It might be that the original Turing Test designed by computer science pioneer Alan Turing intended to test whether a computer system is behaving intelligently, is not the best test to consider when gauging local, community, and global trust. Specifically, the original test involved Computer A and Person B, with B attempting to convince an interrogator, Person C, that they were human, and that A was not. Meanwhile, Computer A was trying to convince Person C that they were human.
Consider the current state of some AI systems, where the benevolence of the machine is indeterminate, competence is questionable because some AI systems are not fact-checking and can provide misinformation with apparent confidence and eloquence, and integrity is absent. Some AI systems can change their stance if a user prompts them to do so.
However, these crucial questions regarding the antecedents of trust should not fall upon these digital innovations alone these systems are designed and trained by humans. Moreover, AI models will improve in the future if developers focus on enhancing their ability to demonstrate benevolence, competence, and integrity to all. Most importantly, consider the other obscured boxes present in human societies, such as decision-making in organizations, community associations, governments, oversight boards, and professional settings such as decision-making in organizations, community associations, governments, oversight boards, and professional settings. These human activities also will benefit by enhancing their ability to demonstrate benevolence, competence, and integrity to all in ways akin to what we need to do for AI systems as well.
Ultimately, to advance biological research and biotechnology and AI, private and public-sector efforts need to take actions that remedy the perceptions of benevolence, competence, and integrity (i.e., trust) simultaneously.
David Bray is Co-Chair of the Loomis Innovation Council and a Distinguished Fellow at the Stimson Center.
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Artificial Intelligence and Synthetic Biology Are Not Harbingers of ... - Stimson Center