THE REAL UPDATE ON THE FAST-MOVING ARTIFICIAL INTELLIGENCE INDUSTRY

A Good News REview Feature, “On the Shoulders of Transformative Technology”

BY HAROON PAREKH

The Good News REview, as the medium to memorialize the Roberts Elementary history, believes that technology is an integral piece of our Roberts history. Technology is transforming everything we know – whether we know it or not. And we would rather know it! So, in this inaugural feature, we will explore artificial intelligence.

I sat down with Dr. Xaq Pitkow, who did his Ph.D. in BioPhysics at Harvard University and is an Associate Professor of Neuroscience and Electrical and Computer Engineering Associate Professor of Neuroscience at Rice University. He is also the co-Director of the Center for Neuroscience and Artificial Intelligence at Baylor College of Medicine.

Ok Xaq, can you tell me a little bit about your job?

My primary goal is to understand the principles of intelligence. In those principles, if they really are principles, they should apply whether it’s a natural intelligence like this one (that our brains produce) or an artificial intelligence like in a computer. So, I try to understand both of them and how they relate to each other.

What is it like to be a researcher of artificial intelligence (AI)?

It’s very exciting! It’s very hard. Most of what we try, like 95%, doesn’t work, so you have to love figuring out puzzles and the experience of trying to figure things out. If you enjoy that

(puzzles), like I do, then it is a good job. It’s also very exciting because so many things are happening in AI right now. Like you may have seen, all the new things that computers can do with all the new training, like making beautiful images, typing back to you, and answering good questions in a way that sounds like it can understand language. You see new things all the time right now and that’s very exciting.

What impact do you think AI will have on the world in the next five years?

That is a wonderful question. I think it’s going to change a lot, and it’s only limited by our creativity. I find it really hard to predict. I would not have thought that language models like chatGPT would be doing nearly as well as they are right now, but when you train enormous models with trillions of parameters, new things emerge that you didn’t think were possible. I think the old way of searching for information will go away. I think you will just talk to your computer and ask it questions. You’ll be able to hold up things to the computer and ask questions, like, “What’s this thing?” and “How do I put it together?” Then, the computer will be able to answer those questions. I think that’s very close. I have friends who are working on those kinds of things right now. I think you will see a lot of cool new applications in video, sound, music, art, ordering things, and in the way you interact with people. There are also some challenges that will be magnified, like misinformation.

What is misinformation?

Misinformation is when people send out bad (or false) information in order to change people’s minds the way that they want. That becomes much easier when you have artificial intelligence. For example, you know you are not supposed to give your password to anybody, but someone really tries to trick you by saying it’s for your benefit, to fix some problem that you have, and to get you something that you want.

Now, all of a sudden, you have a computer program that sounds like a person. You can just send a lot of emails to a lot of people, and you are going to fool some of them into giving out their personal information like their passwords.

So, there’s going to be a lot of trouble for people using AI for bad purposes, and stealing is one. Another way that it’s really going to change things is some decision-making is going to be helped by computers. For example, to figure out what’s wrong with a patient, a doctor orders a scan and reads it because of his experience and training in reading tens of thousands of scans. AI can be trained on ten million scans so it has more ‘experience’ so doctors will use it as a tool. But AI can make mistakes, and when AI makes mistakes, how do we know if it’s real or fake? We will have to put humanity back into the decision-making.

My mom is a neurologist and sees stroke patients with disabilities every day. How do you think AI could benefit those patients? One way is if you can tell what they want to do like if they’re trying to move and they have trouble moving then you can help them do the movement either with a robot arm or something. Or maybe you can see what they’re trying to do on a computer and have the AI figure out what they intend to do. You can also imagine trying to read their minds by scanning their brain if they’re severely impaired.

What do you think are the dangers of Artificial Intelligence?

It’s very powerful technology and just like any powerful technology, it can be used to help people or to hurt people. So, we have to make sure we are carefully in control of it especially because we don’t really understand what the AI is thinking. We build it so that it learns, but we don’t know what it has learned. We just see what it does.

Do you think AI will take over the world?

I think that it will be a long time before you can replace a human with artificial intelligence, and there are some things that you’ll always want people to do rather than robots or computers. Of course, it will take a while for AI to take over and completely replace society, and it is a raging debate right now among people that have different opinions about it. So, I don’t know but it’s certainly true that there is significant risk. We should all be very aware and careful about what we are doing.

What advice do you have for kids who want to be researchers in AI and Neuroengineers?

Stay curious. That is the most important thing. If you just like to figure things out, then you can follow your nose, and the world will tell you all kinds of magical things. If you want some more concrete skills, then learning to program is a great way of starting. Learn math because a lot of the tools that we use to train networks are based on math so that’s really important. Those two skill sets are going to be really useful.

That’s very helpful. Thank you.