Edward M. Lerner Quotes

Making AI more sensitive to the full scope of human thought is no simple task. The solutions are likely to require insights derived from fields beyond computer science, which means programmers will have to learn to collaborate more often with experts in other domains.

I still find it hard to understand that anyone could argue that you can't have machines that exhibit consciousness.

Nobody phrases it this way, but I think that artificial intelligence is almost a humanities discipline. It's really an attempt to understand human intelligence and human cognition.

The sad thing about artificial intelligence is that it lacks artifice and therefore intelligence.

I think Lenat is headed in the right direction, but someone needs to include a knowledge base about learning.

Look, when AIs come up, they're not going to be like us. A self-aware, sentient AI is not going to be like a human.

It's hard to say how far we are down the road to our conventional understanding of artificial intelligence, but I think what we've developed so far, if it's not already consciously awake and hiding from us because it's seen what an ugly and destructive race we are, and it's trying to preserve itself, it's probably in a state of dreaming.

Robots will someday, or maybe, wake up. They may be really smart. They may be as creative, smart and capable as human beings, and fully conscious, and self discerning with free will.

Computers ought to help people find their own best path through lots of textual information.

Twenty-five years ago, the notion was you could create a general problem-solver software that could solve problems in many different domains. That just turned out to be totally wrong.

Interactive computers and software will, I think, provide a less costly method of doing some kinds of inquiry, in knowledge acquisition and even reasoning and interaction.

Language is too complex for a computer to understand. It's not going to be able to make sense of what people are saying en masse. We need a new type of discipline that puts together computer scientists and social scientists, who can add context to the situation.

I'm working on artificial intelligence. Actually, natural language understanding, which is to get computers to understand the meaning of documents.

If we ever find out how the brain works, with all its complexity, then we will be able to build a machine that has consciousness. And if that happens, that is a road to planetary disaster because everything we've thought about ourselves, since the Bronze Age, the Bible, all of that will be gone.

We have to make machines understand what they're doing, or they won't be able to come back and say, 'Why did you do that?'

I believed in realism, as summarized by John McCarthy's comment to the effect that if we worked really hard, we'd have an intelligent system in from four to four hundred years.

We've seen computers play chess and beat grand masters. We've seen computers drive a car across a desert. But interestingly, playing chess is easy, but having a conversation about nothing is really difficult for a computer.

There are three basic approaches to AI: Case-based, rule-based, and connectionist reasoning.

The big question society will have to answer is whether it wants computers thinking like humans.

There is no such thing as transparent intelligence.

I believe there is something going on in a conscious being, which includes many animals, as well as ourselves, that is not a computational activity. And to be conscious at all is not a quality that a computer as such will ever possess - no matter how complicated, no matter how well it plays chess or any of these things.

I definitely fall into the camp of thinking of AI as augmenting human capability and capacity.

Many researchers are exploring other forms of AI, some of which have proved useful in limited contexts; there may well be a breakthrough that makes higher levels of intelligence possible, but there is still no clear path yet to this goal.

In much of computer science, I can easily 'auto-grade' your work and give you an instant meaningful feedback. I can't do this when it comes to the subtlety of human thought, language, poetry, philosophy.

The deep learning techniques, while relatively easy to learn, are quite foreign to traditional engineering modalities. It takes a different mindset and a relaxation of the presumption of control. The practitioners are like magi, sequestered from the rest of a typical engineering process.