Is the IPCC Model the Answer to Regulating AI?
As we continue to make exponential gains in artificial intelligence, there is a growing concern regarding the need for regulated coordination at a global scale. With many experts warning about the dangers and potential impact of AI technology on human society, there is now a proposal to adopt a framework akin to the ones developed to combat climate change.
This article explores whether or not the IPCC model is an appropriate solution for tackling the issues associated with AI, delving into the challenges this might entail and the critical factors that make these two problems inherently different.
The IPCC Model
The IPCC (Intergovernmental Panel on Climate Change) was established in 1988 to provide scientific evidence, guidance, and recommendations on how to combat climate change. Its primary function is to bring together scientists and policymakers from around the world to identify emerging issues, provide a consensus around climate science, and develop pathways toward mitigating impacts resulting from climate change.
The model entails the creation of an intergovernmental panel on artificial intelligence, which would follow an analogous model to the IPCC’s approach, offering a comprehensive framework to address the global regulatory needs for AI.
Why is the IPCC Model Relevant to AI Regulation?
Artificial intelligence is a global problem; it is, therefore, imperative to have a mechanism for coordinated and standardized regulations and guidelines. The IPCC model has gained interest for two reasons: first, climate change and AI share the same inherent global impact. Second, the IPCC model has shown efficacy in creating scientific consensus, which is critical for creating globally coordinated regulation.
However, there are notable differences between climate change and AI, and experts have pointed out that not all aspects of the IPCC model would be appropriate for regulating AI. First and foremost, AI technology is evolving at a rapid pace in comparison to the rate of climate change. This significant difference in the rate of innovation and change in AI technology would require a more agile regulatory framework than that of the IPCC. Additionally, the effect of climate change is pervasive and long term, while AI’s impact can be more immediate but fragmented and localized.
Benefits of Utilizing Similarities between Climate Change and AI
Despite the differences, there are benefits to utilizing the similarities between the two problems by leveraging the learning from the climate change movement to create a foundation for AI regulation. A few of these benefits include:
1. Using insights gained from the climate change experience to prioritize the most critical areas in AI regulation.
2. Building off the collaborative infrastructures developed for addressing climate change such as bringing together global regulators to exchange ideas and strategies.
3. Creating a mechanism for the scientific community to debate and come to a consensus on key issues related to AI.
4. Jointly incentivizing businesses, governments, and individuals to move forward with coordinated action to regulate AI in a manageable yet effective way.
Conclusion: Is the IPCC Model the Solution?
While the IPCC model provides a potential framework for regulation, it falls short in addressing the unique challenges and rate of change in AI technology. The development of a regulatory framework mapping onto AI, will have to be uniquely suited to the fast-paced and innovative nature of this technology.
In conclusion, regulatory bodies must focus on creating nimble, cooperative frameworks for AI regulation, taking inspiration from the IPCC model while also recognizing the fundamental differences that exist between the two problems.
Summary
The proposal for adopting a framework akin to the IPCC Model to regulate Artificial Intelligence is gaining momentum. However, while the similarities between climate change and AI are clear, the rate of change in AI technology is generating unique challenges that require swift, agile, and cooperative regulation. While there is interest in creating a global regulatory framework for AI regulation, whether the IPCC model is ideal remains to be proven. It will require cooperation between experts and policymakers to create an innovative regulatory framework that is adequately suited to the tech and ecology of the AI.
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It’s a phenomenon unleashed by humans that could reshape life as we know it. Worrying warnings from experts have galvanized public concern about it. Meeting rooms are rushing to figure this out. Young people fear it will ruin their future. Governments are making rules to tame it.
Yes, this is advanced artificial intelligence. But it also describes another, more familiar threat: climate change.
This year, as runaway gains in AI technology require globally coordinated regulation, some experts think we should borrow from the international playbook for tackling climate change. And they are right to do so, up to a point. Both problems are inherently global, so a patchwork of national controls won’t work.
But future generations won’t thank us for a repeat of the pitfalls that have dogged attempts to control climate change over the past three decades, especially given the huge benefits AI promises.
Used well, AI could transform our handling of cancer, poverty and even climate change itself. Global warming, on the other hand, has few upsides. A warmer world could make farms more fruitful and extreme cold less risky in some places. But authoritative scientific reports from the United Nations Intergovernmental Panel on Climate Change state clearly that for human health alone, there are very few examples of beneficial outcomes from climate change on any scale.
Few question the conclusions of these reports, but imagine how difficult it would be to coordinate efforts to reduce carbon emissions if there weren’t such a scientific consensus. Artificial intelligence experts don’t need to imagine. They are deeply divided, politically and technologicallyon how much damage it could cause to whom within when, and how much already exists.
So there is understandable interest in seeing if the IPCC model could work for AI. “This is really an active question among policymakers right now,” Professor Robert Trager, of the Center for the Governance of AI, tells me.
That makes sense, though considering the breakneck speed of AI advances, an intergovernmental panel on artificial intelligence should be far nimbler than its predecessor on climate, which typically took about six years to release its mammoth reports.
Furthermore, the IPCC is part of a larger global climate picture that offers many lessons about what Not do for artificial intelligence.
The panel was established in 1988, a year of climate shifts that mirror many of those we’re seeing for AI in 2023. In both years, respected experts issued shocking warnings. In 1988, NASA scientist James Hansen testified in the US Senate that “the greenhouse effect has been detected and is now changing our climate.” This wasn’t the first official global warming wake-up call, but it made front-page news and bolstered early efforts to tackle carbon emissions.
Something similar happened in 2023 as Elon Musk, Apple co-founder Steve Wozniak and more recently the “godfather” of AI Geoffrey Hinton they warned of the risks to humanity posed by technology.
This month alone, the G7 called for new standards to keep AI “trustworthy,” while the White House, United States Senate and 10 Downing Street met with AI bosses to discuss their controversial technology. Meanwhile, the EU is finalizing a groundbreaking AI law aimed at making systems more secure and transparent.
However, there is growing consensus on the need for international collaboration on AI. Some like the International Atomic Energy Agency model. Others prefer the less intrusive example of the International Civil Aviation Organization. It is a United Nations agency, which also houses the climate secretariat that emerged after world leaders backed an international treaty to combat climate change in 1992.
Annual meetings of the treaty’s “conference of the parties,” or COP, led to the setting of more detailed climate goals in the 1997 Kyoto Protocol and the 2015 Paris Agreement. Yet today emissions remain at record levels. The reasons for this are complex and many, but it didn’t help that the climate COPs gave new meaning to the word ‘glacial’.
This is partly because COP decisions do indeed require consent from nearly 200 countries – a recipe for hopelessly slow progress and more. In 2018, Trump administration officials helped prevent a COP meeting from embracing the conclusions of an IPCC report commissioned at an earlier meeting.
Climate COPs serve a number of useful purposes. We would be much worse off without them. But they also show what needs to be avoided as we look for ways to ensure AI works for us, not the other way around.
https://www.ft.com/content/a04a0b31-365b-429f-afed-1bf9393f22ae
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