This piece, Most engineers are white — and so are the faces they use to train software – Recode, implies that AI software doesn’t do a good job recognizing non-white faces because most engineers (i.e. software developers) are white. I’d argue that the AI does a poor job because of this: the developers aren’t very good.
Good software developers, in particular the lead developers, take an active role in ensuring they have good test data. The success of their software when it goes live is dependent on it. Anyone using training data (i.e. using test data) in AI projects that is not using a broad set of faces is doing a poor job. Period. Regardless of whether or not they are white.
If the AI is supposed to do something (i.e. recognize all faces) and it does not, then the AI sucks. Don’t blame it on anything but technical abilities.
Because if you don’t have augmented intelligence, and if you solely depend on AI like software, you get problems like this, whereby automated software triggers an event that a trained human might have picked up on.
AI and ML (machine learning) can be highly probabilistic and limited to the information it is trained on. Having a human involved makes up for those limits. Just like AI can process much more information quicker than a limited human can.
See the link to the New York Times story to see what I mean.
Interesting article: How IBM Watson helped Time magazine narrow its search for Person of the Year (IT Business)
From a technology point of view, it is also interesting that the IBM partner was using IBM’s Watson and Bluemix technologies.
I am biased here, as someone who works for IBM and believes in these technology, but I do think that if you think A.I. and cognitive doesn’t have a place in your business, you should read this. In the next two years, expect all your competitors to adopt these new technologies to compete with you.
Posted in IT
Tagged AI, cognitive, IT, Time, Watson
This piece, 1.8 million American truck drivers could lose their jobs to robots. What then? (Vox) is a great primer on self driving trucks and how they are going to have a major impact sooner than later.
If you are interested in IT, AI or robots, it really shows one of the places where this technology is going to have a significant impact.
If you are interested in economics, politics, or sociology, then the effect of robots replacing all these truck drivers is definitely something you want to be aware of.
If you drive on highways, you definitely want to know about it.
In any case, it’s a good piece by David Roberts. That is his beat and I find he always does a great job of breaking down a topic like this and making it easier to understand and relevant to me. I recommend any of his pieces.
If you want a better understanding of artificial intelligence or if you want to gain some insight into the future of machine learning, I recommend these two free reports, found here: Free AI Reports from O’Reilly Media. There’s so much hype and speculation about AI: these reports cut through all that noise and they will give you a better understanding of what A.I. really is and where it is going.
P.S. If you like them, check out the many great non-A.I. related reports as well. You don’t have to be a technologist to be able to read them.
I have thought a lot about Waze since I started using it. Without a doubt, it has improved my life substantially. Here are some other thoughts I had as I used it.
- Waze is an example of how software will eat the world. In this case, the world of gPS devices. Waze is a GPS on steroids. Not only will Waze do all the things that a GPS will do, but it does so much more, as you can see from this other Waze post I wrote. If you have a GPS, after you use Waze for a bit, you’ll likely stop using it.
- Waze will change the way cities work. Cities are inefficient when it comes to transportation. Our work habits contribute to that, in that so many people commute at the same time, in the same direction, on the same routes, each work day. Waze and other new forms of adding intelligence to commuting will shape our work habits over time. Drivers being able to take advantage of unbusy streets to reduce congestion on major thoroughfares is just the start. City planners could work with Waze to better understand travel patterns and travel behaviour and incorporate changes into the city so that traffic flows better. It’s not that city planners don’t have such data, it’s that Waze likely has more data and better data than they currently have.
- Waze is a great example of how A.I. could work. I have no idea how much A.I. is built into Waze. It could be none, it could be alot. It does make intelligent recommendations to me, and that is all I care about. How it makes those intelligent recommendations is a black box. Developers of A.I. technologies should look at Waze as an example of how best to deploy A.I. Those A.I. developers should look at how best A.I. can solve a problem for the user and spend less time trying to make the A.I. seem human or overly intelligent. People don’t care about that. They care about practical applications of A.I. that make their lives better. Waze does that.
Posted in apps, IT, software
Tagged AI, apps, cities, commute, commuting, GPS, IT, planning, software, travel, Waze
This article, Datasets Over Algorithms — Space Machine, makes a good point, namely
…perhaps many major AI breakthroughs have actually been constrained by the availability of high-quality training datasets, and not by algorithmic advances.
Looking at this chart they provide illustrates the point:
I’d argue that it isn’t solely datasets that drive A.I. breakthroughs. Better CPUs, improved storage technology, and of course new ideas can also propel A.I. forward. But if you ask me now, I think A.I. in the future will need better data to make big advances.
Posted in ideas, IT
Tagged AI, ideas, IT, software