Altman and Amodei address UN: 'There are many things that AI cannot and should not automate'

Altman: AI's promise and anxiety

00:00There are many things that AI cannot and should not automate. AI should be built for people, not simply to turn the crank crank of the machines faster for their own sake. Some of the things people working to build AI have said are so dystopian that they sound like the plot of bad science fiction movies. Anything this power is also powerful is also intimidating. This moment is complicated as we feel both tremendous potential and the very understandable anxiety at the same time. These models can help people discover new knowledge, new medicines, better health care, stronger education, and build more productive economies. They can be new tools for people to pursue dreams and ambition that today feel out

Risks of autonomy and self-improvement

00:38of reach. The complexity of life has increased so dramatically for the average person. AI can be a defensive tool against this complexity as much as it can be this tool of unprecedented discovery and innovation. On the other hand, as AI systems become more capable and more autonomous, they could move faster than our institutions, concentrate power in two two few hands, or make decisions that people no longer understand or control. That concern becomes especially important as we approach systems that can improve themselves and future versions of themselves, often called recursive self-improvement. As the process of building AI becomes more automated, the pace of AI progress could accelerate rapidly.

Two ways AI progress could go badly

01:23This moment calls for extreme care. I largely agree with Professor Bengio, uh although I'll say two instead of three. I believe there are two ways that AI progress could go very badly that we have to avoid. First, we could lose control of the future to AI. The risk is that it moves so fast that people can no longer follow what's happening or intervene when needed. This would obviously be terrible. The industry must not accept too much technological risk just because the benefits are too great and that they feel too important to slow down. Beating companies in a competitive race is not a reason to make rash decisions, nor do we believe we are locked in a race where we are unable to do that. We

02:01have unilaterally slowed down in the past. We will do so in the future. We do not want to build systems. We think it's important that everyone avoids building systems where we cannot make the alignment, monitorability, and safety guarantees that we must. We need to understand what these systems are doing and have strong evidence that they will do what people intend even as they get very, very smart. Actually, especially as they get very, very smart. It doesn't matter whether people put the risk of catastrophe at 10% or 1% or 12% or 0.1%. None of these levels are remotely acceptable. And we should not train models that we cannot make an extremely strong case they will be able to keep under human control.

OpenAI's three principles

02:37So, that's one way things can go wrong. In the other direction, these systems could concentrate too much power in too few hands. No one person or company or country should be able to use the most powerful AI models to impose their worldview on everyone else. A company or country that believes only it can be trusted with this technology can use that belief to justify almost anything else. We have to reject that logic even when it is convenient for any one actor. I believe there is a pragmatic path through both of these. At OpenAI, we approach these questions with a clear goal. AI should give people more power over their own lives, more freedom to live lives the way they want, more ability to solve problems big or small, and to

03:19improve their communities. We don't want to fall into the trap of blind optimism. We also don't want to fall into the trap of doomerism, either. Getting pulled into either extreme will not help us successfully figure out the challenges in front of us, especially at a time when the world and its people face such enormous challenges that this technology can help solve. So, we try to walk the middle path between these two poles. For us, that means three principles. First, as AI becomes more capable, people must remain at the center of AI decision-making. Alignment is not an abstract research question. It is the work of ensuring that these systems reliably remain under human control, reflect human values, and help people

03:59guide the next stages of development. We are not trying to and must not automate human judgment or human values. Second, the benefits of scientific progress and economic growth must be by people and for people. AI should help researchers make discoveries, doctors treat patients, teachers teach students, entrepreneurs start companies, communities solve problems that felt out of reach, and much more. The continuous story of human progress is not the tools replace human agency, it is that the right tools make people more capable, and I believe this is going to go much further than we believe possible. Third, this technology must empower people individually. A great future will come from people realizing their potential and building

Math progress and the Navier-Stokes result

04:39value for themselves, their communities, their countries, and the broader world. We might be with the builders, one of the builders of this technology, but we are not the heroes of this story. Our role is to enable people all over the world, and to trust in the magic of humanity's skill and faculties. We now have models capable of discovering knowledge that we have never had before. Consider the progress we've seen in math. Three summers ago, our models were okay at grade school math. Two summers ago, they were pretty good at high school math competitions. Last summer, we reached gold a gold level medal in the most prestigious international math competition. And just a few weeks ago, this summer,

05:18one of our models solved one of the Millennium Prize problems, the Navier-Stokes equations. These equations are used for aircraft design, weather forecasting, and the study of blood flow. We are not solving math problems for their own sake, but to empower people to discover new knowledge, and to use it to improve health care, raise standards of livings of living, and expand everyone's potential around the world. There remains so much to be discovered. But it's very important that companies not substitute for the democratic process. If AI is to be democratic, the most important decisions cannot be made by labs in San Francisco alone. They must be shaped through democratic processes and by governments accountable to the

Call for international standards

05:55people that they serve. At the international level, this will require cooperation. In our history, there have been times where countries who compete and don't always like each other very much still come together for shared interests and the collective good in the face of a powerful new technology. We believe this must be one of those times. We need a mechanism for complementary national and international frontier AI standards. Standards for measuring capabilities, assessing risks, determining whether safeguards are sufficient, and preserving meaningful human oversight as systems become more autonomous. We need common standards so countries can compare evidence, verify compliance, and have a shared language and

06:36understanding about what is happening. We need accurate and speedy incident reporting, classification and reporting protocols so the world can learn from failures before they become catastrophes. And we need secure channels among governments, critical infrastructure operators, and technical experts to share emerging vulnerabilities and new threats. Obviously, these standards should not lock in incumbents or favor one business model over another. They must support open and closed model developers, new entrants and established labs, national authority, and international cooperation. Each government should decide how to incorporate standards into its own legal system, but we will all be better off if

The crossroads: two possible futures

07:15we can agree on what good evidence, good safeguards, and good oversight look like on the global stage. We do not have all the answers, and we're very open to any better ideas. We're ready to work with you all and try our hardest to figure out the path forward. We are at a crossroads. One path leads to a world where power is concentrated, decisions are opaque, and people feel that the most important technology of their lifetime is something being done to them. The other path leads to a world where AI works for people because people, through democratic institutions, help decide how it should develop and guide it. Where scientific progress improves real lives, where more people can participate in the

Amodei: rapid progress and benefits

07:54future, and where this technology continues to give individuals and communities greater power to live life as they choose. This is a future of realized potential, excitement, and wonder, and it is the future we believe is worth building. Thank you very much. >> I thank Mr. Altman for his briefing. I now give the floor to Mr. Dario Amodei. >> Good afternoon. I'd like to thank France for convening this meeting and the members of the council for inviting me to speak. AI is advancing very quickly. Four years ago, it could barely write a line of code or solve a high school math problem. Today, it writes most of the code at Anthropic and solves world-famous unsolved math problems. The trajectory only needs to continue for a

08:38tiny period longer, one or two years, maybe less, to reach what I've called a country of geniuses in the data center. This rapid pace of progress will produce incredible benefits for the world. Just today, Anthropic announced the Claude-led discovery of a new molecular machine. It's a preliminary finding, but it may constitute a new gene editing mechanism that could have applications in in gene therapy. Claude led the literature review, theorizing, and experimental design, and humans ran and verified the experiments in the lab. We believe this type of application will accelerate rapidly in the years ahead and that we can make profound progress in the near future on diseases that have plagued humanity for millennia.

Two categories of risk

09:21But these remarkable capabilities also come with risks that must be managed. I see two main categories of risk. The first is misuse of AI models, for example, misuse by bioterrorists to create biological weapons. The second risk is loss of control. Model capabilities accelerating beyond developers' ability to control them. These questions are global in scope and concern all of humanity. They are grave enough that I believe they are important questions for this council, not just for economic or ICT ministries. If managed poorly, I even believe that AI could be a risk to humanity as a whole. At Anthropic, we believe we have the best track record in the industry for preventing these risks, both operationally and in our research. We

Anthropic's safety practices

10:06test every model for dangerous capabilities in areas like cybersecurity and biology. We put strong safeguards on our most capable models, and we publish our work in these areas. We have pioneered research in areas like mechanistic interpretability and alignment science that improve our ability to steer and control our models. We also have unparalleled transparency practices, releasing risk reports that run to hundreds of pages. But we understand that as AI models become more powerful, even more stringent standards of safety will be required. And we are always aiming to improve our safety and alignment practices, our abilities our ability to prevent misuse, and we are always striving to do better. We will

Pacing the frontier and global cooperation

10:50slow down as much as necessary in order to make sure that every successive AI technology that we release is actually safe. But regardless of what we do, managing these risks is ultimately bigger than anyone company. And it has an industry-wide and global scale. On September 12th, I called for a collaborative effort to pace the frontier, not to stop AI progress, but to work together to make sure the industry and the world can proceed at a rate where we can be sure that safety keeps up with capability for everyone in the industry. This call had three parts. First, we committed to embed external evaluators inside Anthropic with employee-like access, similar to a food inspector. And And we recommended that other companies

11:39across the world do the same. Some have already agreed uh to adopt this measure. Second, we called for cooperation across the industry to set standards and modulate the pace of progress. And finally, we called for global cooperation across the world between governments to set international standards. It is this last area that most squarely falls within this council's remit. I want to offer three ideas in this regard. First, we should begin with narrow agreements that every member can support, such as a ban on using AI to make biological weapons or permitting your AI technologies to be used to make biological weapons. Second, we should build evaluation and verification systems that keep pace with

Three proposals for the Security Council

12:30AI development so that states can have visibility into frontier model capability and can verify each other's commitments. Third, we should establish common global standards for testing AI models for loss of control risks and misuse risks, and a notification system for AI incidents that are significant to global security. I believe that this is the most important global security issue facing the world today. For all the differences of the people in this room, we must put aside those differences in order to confront this global opportunity and global threat that is being presented to us at the same time. No leader, no company, and no nation can manage this alone. We commit to working with governments in

13:18this room on this urgent work. Thank you for your attention.