500 days of Artificial Intelligence #1

I am challenging myself to write and think about the topic of artificial intelligence for the next 500 days with the #500daysofAI.

This is inspired by the film 500 Days of Summer where the main character tries to figure out where a love affair went sour, and in doing so, rediscovers his true passions in life.

Day 1 — Defining Artificial Intelligence

During the last few years particularly there has been a growing interest for artificial intelligence (AI) around the planet. From the promising applications within healthcare to the ongoing AI arms race this raises both a series of possibilities as well as risks. One thing we know for certain is that there might be a need to understand what common definitions AI contain when its use is becoming so widespread.

In this regard it may be useful to begin diving into a basic level of comprehension. This rudimentary level of understanding is where I currently find myself. I have found the Elements of AI course to be of great help in this regard. As such what I discuss here in this first part will likely be a lesser version of the information provided in this course mixed with some of my own thoughts and opinions. I strongly encourage you to sign up to this free course, and do please tell me if it helps you as well.

Both artificial and intelligence can be notoriously difficult to define, as such combining the two does not make the level of confusion any less.

Not artificial general intelligence (AGI)! We are not talking about AGI that can do whatever a human can do. No, and yet some applications of AI can do more than a human would be able to do, such as analysing hundreds-millions of pictures in a very short span of time. This brings us to an oppositional pair in representing AI.

Narrow/weak/applied or broad/strong AI? Narrow AI or applied AI is the use of software to study or accomplish specific problem solving or reasoning tasks. Perhaps it can be said that Applied AI in this sense is the most common usage and easier to define than its counterpart broad/strong AI which has been said to at time border towards thoughts of AGI — more capable of experiencing consciousness.

Autonomy: the ability to perform tasks in a complex environment without constant guidance by a user. This seems straightforward — yet again there has been large discussions on the notion of autonomy in fields ranging from computer science to feminist philosophy. As well in other fields of philosophy autonomy is an informed, uncoerced decision. There are questions arising in regards to active or passive applications or perceptions of A.I.

Adaptivity: the ability to improve performance by learning from experience.

As such from a very short introduction and diving into the terminology within the field of artificial intelligence we can see that attempting to understand the basic outline can be relatively problematic in itself.

Marvin Minsky a cognitive scientist and one of the greatest pioneers in AI, coined the term suitcase word for terms that carry a whole bunch of different meanings that come along even if we intend only one of them. Using such terms increases the risk of misinterpretations such as the ones above.”
-Elements of AI part 1: How Should We Define AI

As such saying artificial intelligence does in itself bring up a field of related subject areas and will inevitably lead to misinterpretations. We can imagine leaders in politics and business discussing these terms without a common or basic understanding of some elements of AI with great vigour. Perhaps this is an event that you have already have experienced first-hand?

If so it is understandable – as it is unfair to require most people to understand the basic concept of artificial intelligence, although Finland and Sweden has challenged each other with ambitious goals for a percentage of their population to do so. Can most of your friends explain how the Internet works or their phone works? It is unlikely that they can do this in detail, depending on your friends.

Again, when it comes to definitions there is additionally the classificatory opposition of AI vs. non-AI that is in no way absolute neither legal nor definite in research terms. Additionally it is not a countable noun, it is a field of research, as such saying that you need more or less AI could be wrong. Elements of AI suggest that we talk about AIness (as in happiness or awesomeness). Will we however hear anyone talking of AIness? Time will tell.

Starting a navigation through or within the field of artificial intelligence seems like a daunting journey to set out on. It does not either seem like a straightforward journey with one destination.

Parts of humanity’s current love affair with AIness is thrilling to watch. It remains to be seen whether this love will flourish or turn sour in the years to come. Who knows.

This is day one.

AI Policy and Ethics at www.nora.ai. Student at University of Copenhagen MSc in Social Data Science. All views are my own. twitter.com/AlexMoltzau