Humour me and imagine, if you will, some years in the not too distant future: you are part of a group putting your attention to understanding something. Somewhat like you might be doing now.
Not everyone in your group is human.
We are not talking about alien life here. We’re not talking about animals either. No. Imagine for instance this particular fellow group member is an “intelligent agent”.
There are various definitions of an intelligent agent. For this case, let’s say that an intelligent agent is a device that perceives its environment and takes actions to maximise its chance of success.
An intelligent agent is a type of thing we more generally call artifical intelligence, or AI.
AI has arrived. What is AI?
AI and intelligent agents are changing the way we live and work.
Let’s think about this concept of intelligence. What is intelligence? Well, the Oxford dictionary defines it as “the ability to acquire and apply knowledge and skills”. Other definitions include: self-awareness, emotional knowledge, and capacity for logic. For our purpose of discussion, I’m going to define intelligence here as “the ability to achieve complex goals“. This definition broadly covers all of those ideas. There are many goals and the ability to achieve them provides a basis for intelligence.
Intelligence comes on a scale. The degree of ability to achieve a goal helps us understand where on the spectrum of intelligence something is. A complex goal might be: speaking. Let’s consider. Can a baby speak? No. Can an adult speak? Yes, generally. What about a child? All are somehwere different on the spectrum of intelligence.
Intelligence is narrow or broad. IBM’s Deep Blue chess computer beat the chess grandmaster Gary Kasparov in 1997. It could beat a chess grandmaster at chess but in noughts and crosses (a.k.a. tic-tac-toe), it couldn’t beat a 4-year old. It was built with a narrow focus of ability.
The more recent Google Deep Mind DQN AI system can play dozens of vintage Atari games at human level or better. This system is built to be able to apply itself to new goals. We might consier it has a broader capacity for intelligence.
Humans however, we as a species are so far unique in all the world with reagrd to intelligence. We are able to master a huge amount of skills. We can learn languages, sports, vocations and so much more. There’s nothing on the planet to rival us at this point in time.
General AI is coming
We are seeing accelerated breakthroughs and uses of AI in broader areas of our lives. Research and development in artificial intelligence has an endgame focus of general AI at a human level. Narrow AI will eventually evolve to become general AI. Whilst we do not know when this will happen (and some do question whether it will ever happen), there is no doubt of the advances and applications of AI.
Deep Mind has been able to learn many different games by using a positive reinforcement deep learning technique called reinforcement learning. This is a general unsupervised learning technique that computers use to teach themselves how to achieve narrow goals.
Using this technique, Google Deep Mind has been able to master and outplay human testers on 29 different vintage Atari games. Never sleeping, never resting and with no need to eat, computers can spend almost endless time learning how to achieve their goals in virtual reality, and then apply that knowledge when ready.
AlphaGo demonstrated strategic creatvity when it beat Lee Sedol, considered the top player of Go in the world in 2016. It was expected to take another decade before AI beat a human Go champion. AlphaGo went on to beat all 20 top players the year after it beat Lee Sedol.
To put this feat in context… there are many more possible Go positions than there are atoms in the entire universe. Therefore players rely heavily on intuition alongside conscious analysis. AlphaGo shocked the world by defying ancient wisdom by playing on the 5th line early in its 2nd game against Lee Sedol, and it went on to win the game. This was a demonstration of intuitive / creative play from a machine-based atrtifical intelligence.
AI is being widely used throughout our lives today
Natural language translation was not really considered possible when I studied AI back in the 1990s. As a student of computer science at university I recall discussing computation ability and we considered it as unable to cope with the ambiguities of natural langauge back then. Now we see natural language translation all around us. We are now seeing translation happen in real-time as well. What other examples do we see of AI all around us?
AI is being used in finance. Most stock market buy-sell decisions are now made automatically by computers. Algorithmic trading is the AI behind this. Algorithmic trading is used to help profitable trading. It allows resources to be efficiently allocated across the world at the speed of light.
In healthcare we are seeing changes in multiple areas, like diagnosis and surgery:
- In 2015 a Dutch study showed that computer diagnosis of prostrate cancer using MRI was as good as human radiologists
- In 2016 a Stanford study showed AI could diagnose lung cancer using microscope images better than human pathologists could
- Machine learning is now used in medical research institutes such as Walter Eliza Hall Institute, for instance in predictive modelling for best outcomes based on analysis of genes, diseases and treatment responses
- 2 million robotic surgeries have been performed in the US smoothly between 2000 and 2013 according to a recent report in 2017
We are in the midst of the 4th industrial revolution. AI is one of the catalysts in this step change for humaity.
AI is now a permanent part of our lives, changing the way we live and work
Let’s review what we’ve covered.
Artificial Intelliegence has arrived. What is AI? It is a narrow, limited ability to achieve a goal, at this point time (2021). The engame is a broader, more capable ability to achieve complex goals.
General AI is coming. Accelerated breakthroughs have shown advancements in intuitive, creative, strategic mastery of games. Virtual reality is now commonly used for reinforcement learning in training AIs.
AI is widely used today for the positive benefit of human society. In finance and healthcare we are seeing improvements that benefit humans.
Imagine who’s listening
Imagine some time in the not too distant future, you’re part of a group putting your attention to understanding something. Not everyone in your group is human…
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