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Believing the Data

By Steve Jones,

This is interesting to me. Let's leave aside the moral, ethical, or political sides of this. Let's just look at the data. A cop gave a ticket to a self driving car. Apparently the officer thought the car was within 10 feet of a pedestrian. The logs for the car show that it was 10.4 feet away. A negligible difference to me, but that might matter in a court of law.

As we use digital data more and more to control vehicles, devices, even behavior, we are going to have problems, complaints, and unforeseen issues amongst humans and computers. Certainly our laws need reforming to deal with the digital world, but we also will have some cultural transformations to undertake.

Much of our arbitration in the world has dealt with how well humans argue or debate topics. We are inconsistent, easily confused creatures, yet we often use our judgment and impressions to make decisions about whether we believe one individual over another. This has often been the case in law, even as more science with cameras, DNA, and other forensic techniques have tried to provide definitive proof one way or the other.

As we use more digital devices, there will be, or should be, more logs and audit records of how systems behave. This worries me a bit in Machine Learning systems, but experts seem to believe we can unpack the rationale for decision making if necessary. In any case, we need to learn to trust and believe in the data, even if our eyes and instincts lead us to different conclusions. This doesn't mean that the data makes the decision, but we can't discard the data because we don't like it. Certainly context matters, and in the original case above, we'd want to consider velocity and acceleration, and possibly other factors to determine if the car was too close.

Ultimately, I believe digital records will start to prevail in more circumstances than we might be comfortable with. We'll slowly change, and likely subsequent generations will trust data more than we do, perhaps even more than their senses. To me, this means that those of us that deal with data systems need to ensure there is extremely strong security and integrity of data records, and that we disclose algorithms and data processing techniques in a transparent way. Trust requires knowledge, which requires transparency. That's something we certainly need to improve on as an industry.

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