AI Policy Considerations for Food, Land, and Water Systems · IFPRI Podcast · Radar

Why AI policy research matters now2:42 – 6:55

2:42

Thanks, Charlotte.

2:44

Hello, everyone.

2:45

Welcome to our seminar.

2:47

We have been planning this event since I think about last January for quite some time.

2:53

But I feel that this discussion just could not be more timely, especially today.

2:58

Just for the last few days, if you follow the news, the people building the world's most advanced AI systems have been calling for greater caution.

3:08

Anthropik has urged a slower pace so safety measures can catch up.

3:13

OpenAI has called for mandatory safeguard.

3:17

A recent incident involving AI systems crossing security boundaries remind us that these concerns are not hypothetical anymore.

3:29

Bill Gates, in his recent essay, raised another important concern.

3:35

Young people could enter a workforce with fewer opportunities while society remains inadequately prepared for the transition.

3:44

Even if you are the most optimistic about AI, these warnings should make us pause for a minute or two.

3:51

We are well beyond the hype.

3:53

AI is already a double-edged sword, a source of so much possibility, but at the same time also a source of new vulnerabilities.

4:02

For us, however, caution does not mean standing still.

4:07

Global challenges like hunger, climate risk, growing inequalities, and pressure on natural resources will not wait for the global AI debate to be settled.

4:21

We should actively explore how AI can make our knowledge more accessible and our policy analysis more responsive.

4:29

We must test these tools in local context, protect people's data and make uncertainties more visible, and keep researchers and policymakers accountable.

4:41

Most importantly, we must ask whether and how small scale producers and low and middle income countries will help shape this technology for them and share the benefit.

4:54

Whenever a new technology arrives, we researchers have a habit of saying that more research is needed.

5:01

It is almost a reflex.

5:03

But in the case of AI, the reflex happens to be exactly right.

5:08

The technology is moving so fast, faster than our evidence base.

5:13

And the policy decisions are being made whether or not the evidence is ready.

5:18

So we do need more research, and we need it now.

Why AI policy research matters now2:42 – 6:55

2:42

Thanks, Charlotte.

2:44

Hello, everyone.

2:45

Welcome to our seminar.

2:47

We have been planning this event since I think about last January for quite some time.

2:53

But I feel that this discussion just could not be more timely, especially today.

2:58

Just for the last few days, if you follow the news, the people building the world's most advanced AI systems have been calling for greater caution.

3:08

Anthropik has urged a slower pace so safety measures can catch up.

3:13

OpenAI has called for mandatory safeguard.

3:17

A recent incident involving AI systems crossing security boundaries remind us that these concerns are not hypothetical anymore.

3:29

Bill Gates, in his recent essay, raised another important concern.

3:35

Young people could enter a workforce with fewer opportunities while society remains inadequately prepared for the transition.

3:44

Even if you are the most optimistic about AI, these warnings should make us pause for a minute or two.

3:51

We are well beyond the hype.

3:53

AI is already a double-edged sword, a source of so much possibility, but at the same time also a source of new vulnerabilities.

4:02

For us, however, caution does not mean standing still.

4:07

Global challenges like hunger, climate risk, growing inequalities, and pressure on natural resources will not wait for the global AI debate to be settled.

4:21

We should actively explore how AI can make our knowledge more accessible and our policy analysis more responsive.

4:29

We must test these tools in local context, protect people's data and make uncertainties more visible, and keep researchers and policymakers accountable.

4:41

Most importantly, we must ask whether and how small scale producers and low and middle income countries will help shape this technology for them and share the benefit.

4:54

Whenever a new technology arrives, we researchers have a habit of saying that more research is needed.

5:01

It is almost a reflex.

5:03

But in the case of AI, the reflex happens to be exactly right.

5:08

The technology is moving so fast, faster than our evidence base.

5:13

And the policy decisions are being made whether or not the evidence is ready.

5:18

So we do need more research, and we need it now.