The outgoing White House AI director explains the policy challenges ahead

They are making good progress on this and expect to have this framework in place by early 2023. There are some nuances here: different people interpret risk differently, so it is important to come to a common understanding of what risk is and what appropriate approaches may be risk mitigation and what potential damages may be.

You talked about the issue of bias in AI. Are there ways that the government can use regulation to help solve this problem?

There are both regulatory and non-regulatory ways to help. There are many existing laws that already prohibit the use of any type of system that is discriminatory, and that would include AI. A good approach is to look at how existing legislation is applied and then clarify it specifically for AI and determine where the gaps are.

NIST released a report earlier this year on AI bias. They mentioned a number of approaches that should be considered when it comes to governing in these areas, but much of it has to do with best practice. So it’s about making sure that we’re constantly monitoring the systems or that we’re providing opportunities for recourse if people feel they’ve been wronged.

It’s about making sure we’re documenting the ways these systems are trained and on what data, so we make sure we understand where bias can creep in. It’s also about accountability and making sure that the developers and the users, the implementers of those systems, are held accountable when those systems aren’t developed or used properly.

What do you think is the right balance between public and private AI development?

The private sector is investing far more than the federal government in AI R&D. But the nature of this investment is very different. The investment that is happening in the private sector is very much in products or services, while the federal government is investing in long-term cutting-edge research that doesn’t necessarily have a market driver for the investment, but potentially opens up the lead to the mark. -New ways to do AI. So in terms of R&D, it’s very important that the federal government invests in those areas that don’t have that reason that drives industry to invest.

Industry can work with the federal government to help identify what some of these real-world challenges are. This would be fruitful for US federal investment.

There is so much that government and industry can learn from each other. Government can learn about best practices or lessons learned that industry has developed for its own companies, and government can focus on the right guardrails that are needed for AI.

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