Modern artificial intelligence is capable of wonders. It can produce breathtaking original content: poetry, prose, images, music, human faces. It can diagnose some medical conditions more accurately than a human physician. Last year it produced a solution to the “protein folding problem,” a grand challenge in biology that has stumped researchers for half a century.
Copyright by www.forbes.com
Yet today’s AI still has fundamental limitations. Relative to what we would expect from a truly intelligent agent—relative to that original inspiration and benchmark for artificial intelligence, human cognition—AI has a long way to go.
Critics like to point to these shortcomings as evidence that the pursuit of artificial intelligence is misguided or has failed. The better way to view them, though, is as inspiration: as an inventory of the challenges that will be important to address in order to advance the state of the art in AI.
It is helpful to take a step back and frankly assess the strengths and weaknesses of today’s AI in order to better focus resources and research efforts going forward. In each of the areas discussed below, promising work is already underway at the frontiers of the field to make the next generation of artificial intelligence more high-performing and robust.
(For those of you who are true students of the history of artificial intelligence: yes, this article’s title is a hat tip to Hubert Dreyfus’ classic What Computers Still Can’t Do. Originally published in 1972, this prescient, provocative book remains relevant today.)
With that, on to the list. Today, mainstream artificial intelligence still can’t:
1) Use “common sense.”
Consider the following prompt: A man went to a restaurant. He ordered a steak. He left a big tip.
If asked what the man ate in this scenario, a human would have no problem giving the correct answer—a steak. Yet today’s most advanced artificial intelligence struggles with prompts like this. How can this be?
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Notice that this few-sentence blurb never directly states that the man ate steak. The reason that humans automatically grasp this fact anyway is that we possess a broad body of basic background knowledge about how the world works: for instance, that people eat at restaurants, that before they eat a meal at a restaurant they order it, that after they eat they leave a tip. We refer to this vast, shared, usually unspoken body of everyday knowledge as “common sense.”
There are a literally infinite number of facts about how the world works that humans come to understand through lived experience. A person who is excited to eat a large meal at 7 pm will be less excited to eat a second meal at 8 pm. If I ask you for some milk, I would prefer to get it in a glass rather than in a shoe. It is reasonable for your pet fish to be in a tank of water but problematic for your phone to be in a tank of water. […]
Read more: www.forbes.com
Modern artificial intelligence is capable of wonders. It can produce breathtaking original content: poetry, prose, images, music, human faces. It can diagnose some medical conditions more accurately than a human physician. Last year it produced a solution to the “protein folding problem,” a grand challenge in biology that has stumped researchers for half a century.
Copyright by www.forbes.com
Critics like to point to these shortcomings as evidence that the pursuit of artificial intelligence is misguided or has failed. The better way to view them, though, is as inspiration: as an inventory of the challenges that will be important to address in order to advance the state of the art in AI.
It is helpful to take a step back and frankly assess the strengths and weaknesses of today’s AI in order to better focus resources and research efforts going forward. In each of the areas discussed below, promising work is already underway at the frontiers of the field to make the next generation of artificial intelligence more high-performing and robust.
(For those of you who are true students of the history of artificial intelligence: yes, this article’s title is a hat tip to Hubert Dreyfus’ classic What Computers Still Can’t Do. Originally published in 1972, this prescient, provocative book remains relevant today.)
With that, on to the list. Today, mainstream artificial intelligence still can’t:
1) Use “common sense.”
Consider the following prompt: A man went to a restaurant. He ordered a steak. He left a big tip.
If asked what the man ate in this scenario, a human would have no problem giving the correct answer—a steak. Yet today’s most advanced artificial intelligence struggles with prompts like this. How can this be?
Thank you for reading this post, don't forget to subscribe to our AI NAVIGATOR!
Notice that this few-sentence blurb never directly states that the man ate steak. The reason that humans automatically grasp this fact anyway is that we possess a broad body of basic background knowledge about how the world works: for instance, that people eat at restaurants, that before they eat a meal at a restaurant they order it, that after they eat they leave a tip. We refer to this vast, shared, usually unspoken body of everyday knowledge as “common sense.”
There are a literally infinite number of facts about how the world works that humans come to understand through lived experience. A person who is excited to eat a large meal at 7 pm will be less excited to eat a second meal at 8 pm. If I ask you for some milk, I would prefer to get it in a glass rather than in a shoe. It is reasonable for your pet fish to be in a tank of water but problematic for your phone to be in a tank of water. […]
Read more: www.forbes.com
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