Have 2017 Predictions for Artificial Intelligence Come True?

AI Today: We’d like to start by you introducing yourself and telling us a little bit about the things that you’re doing in the field of AI.

Oliver Christie: I’ve been in the field of AI for some time, mostly centered around natural language processing and human insights. What’s the crossover between people and how we act and how AI can better understand that. I’m a consultant so half of my work is done with tech companies and big financial institutions so they can figure out how to implement AI. Then the other half of the work I do is research based thinking about where AI is going, what it’s going to look like next, and how a company might look if it’s re-built from scratch with AI and data.

Now, getting on to the predictions. You can find Oliver’s article that we discuss here: https://medium.com/towards-data-science/5-artificial-intelligence-and-data-predictions-for-2017-2d700fcb1751

Prediction #1: Insight Data will Replace Big Data

Oliver Christie: The first prediction I made was that big data which was quite a loose term would be replaced with insight data. What I meant by that is it’s not particularly useful having an awful lot of data unless you know what that data’s about. I can have any quantity of data in front of me but if I don’t know the function of that and how it is useful the data doesn’t really have much purpose. I think the insights are going to be the things that people really start to talk about a lot more. That part is the valuable part anyway.

Prediction #2: Data in a Post-Truth World

Oliver Christie: Prediction #2 was that how we think about data and post truth world is changed. If we now have the idea that scientific fact or an industry view can be challenged by a large audience easily it doesn’t change the fact that that scientific fact is, on the whole, accurate and right and correct. But there is a disconnect between the scientific community and the general public at large. I think that gap has to be narrowed and it’s very wide at the moment and it’s growing.

Prediction #3: The Public Demand For Information

Oliver Christie: Something I’ve been saying for some time is as humans we’re hungry for information; information on what to buy, what to do, where to go especially for something medical (what treatment should I get). And you’re hungry for the knowledge so you can make the best choice. The Internet is fantastic for providing information but it’s very poor for saying which information is empirically correct. Anyone can publish online at the moment. and it’s very hard to figure out which things are true which things are not true unless you’ve got a very deep understanding of that particular subject, and even if you have a deep understanding of the subject it’s still quite hard which things can be double blind tested. The public is still looking for information. I think for the people the percentage of the population who are interested in knowledge and understanding this is going to ramp up and the demand is going to be higher simply because with more information we should be about to make a better choice. On the flip side though I think there’s also a fairly large percentage of people who are not interested in knowledge who are not interested in understanding wider facts and those people tend to get more and more entrenched in that viewpoint.

Prediction #4: Data Will Become Connected

Oliver Christie: We’ve still got data in silos. We’ve still got individual companies hoarding their own data. But that data in it’s particular silo isn’t necessarily that useful. It will lead you towards one answer for one question but doesn’t necessarily put things into context. So we’re still stuck with a very narrow dataset. With AI we can build off that. It’s still incredibly narrow. We need more data from more places to get a wide understanding of any situation and it’s at that point that AI can really start doing the things that it should be able to be doing.

Prediction #5: Companies Not Using AI Will Get Left Behind

Oliver Christie: Companies who are working on AI now are starting to think about the challenges and thinking about data in new ways. They’re thinking about what the impact is going to be on the structure of their company on the bottom line. They are getting to the problems quicker. They’re also making progress. It’s thinking about these big questions. That’s the challenge. But it’s also if you can tackle them, if you can solve these problems early, you’re way ahead of the competition and I think the competition won’t be able to catch up. I think once you’ve figured out how AI works in your organization and leverage it to do more than just automation, your competition won’t be able to reach to where you are. So yea I really think we’re seeing somewhat of an arms race.

Related posts:

Food insecurity rates are rising rapidly in Marion County. According to the Service Learning Assistant at the IUPUI Campus Kitchen, Ashabul Alam, “43 percent of students at IUPUI are now classified…

While some NFTs do certainly seem like crazy, expensive, digital art, there’s definetly a use case to them which I’ll show you today. Let’s say Ferrari gave people an NFT when buying their cars. That…

Clean building practices are the line of defense against the thoughtless, ubiquitous use of toxic building materials. The Slow Space Movement advocates for buildings that are good, clean and fair…