It will be very tricky to test and regulate safety of self-driving cars

My friend Don Norman wrote an op-ed this weekend calling for an FDA-like testing program before autonomous cars are put on the roads in the US. Clearly, some level of government approval is important. But I see lots of problems with using drug testing (FDA = Food and Drug Administration) as a model.

Here is an excerpt from a recent article about testing problems with Uber cars, which were the ones in the recent fatal accident. After the break, my assessment of how to test such cars before they are allowed on American roads.

Waymo, formerly the self-driving car project of Google, said that in tests on roads in California last year, its cars went an average of nearly 5,600 miles before the driver had to take control from the computer to steer out of trouble. As of March, Uber was struggling to meet its target of 13 miles per “intervention” in Arizona, according to 100 pages of company documents obtained by The New York Times and two people familiar with the company’s operations in the Phoenix area but not permitted to speak publicly about it.Yet Uber’s test drivers were being asked to do more — going on solo runs when they had worked in pairs.And there also was pressure to live up to a goal to offer a driverless car service by the end of the year and to impress top executives.

So Uber car performance was more than 100 times worse than Waymo cars?!

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Hollywood as a model for academic research

Academia has a problem: the value, necessity, and practices of collaboration are increasing, but the system of giving credit is inadequate. In most fields, there are only 4 levels of credit:

  • None at all
  • “Our thanks to Jill for sharing her data.” (a note of thanks)
  • First Authorship (This is ambiguous: it may be alphabetical.)
  • Listed as another author

In contrast to this paucity, modern empirical paper writing has many roles. Here are a dozen roles. Not all of them are important on a single paper, but each of them is important in some papers.

  • Intellectual leadership.
    • Source of the original idea
  • Doing the writing
    • Writing various parts, e.g. literature review
    • Doing the grunt work on the stat analysis. (Writing and running the R code)
    • Doing the grunt work of finalizing for publication. (Much easier than it used to be!)
    • Dealing with revisions, exchanges with editors, etc.
  • Source of the data.
    • Funder of the data
  • Raised the funding;
    • Runs the lab where the authors are employed
    • Source of the money: usually an agency or foundation, but sometimes the contracting author is listed as a coauthor.

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Irrational tax cuts won’t raise long term economic growth

I recently received the following on a Dave Farber’s “Interesting People” list, a collection of techies with interest in Internet policy issues. Why discuss it now, since the tax bill has been passed? It is important for all to realize how much the Republicans in Washington no longer believe in basing their decisions on  reality  (“facts”). It is very hard to believe this, but the evidence is now overwhelming, and the consequences will continue to be grave. I wrote the following quick response.
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It seems completely reasonable and even desirable to take actions such as lowering corp taxes,  lowering taxes on productivity and reducing regulation to get the economy growing at the 3-4%  range.

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Fraudulent academic journals are growing

Gina Kolata in the NY Times has been running a good series of articles on fraudulent academic publishing. The basic business model is an unholy alliance between academics looking to enhance their resumes, and quick-buck internet sites. Initially, I thought these sites were enticing naive academics. But many academics are apparently willing participants, suggesting that it’s  easy to fool many promotion and award committees.

All but one academic in 10 who won a School of Business and Economics award had published papers in these journals. One had 10 such articles.

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What snakes are growing in the Gardens of Technological Eden?

Two emerging technologies are revolutionizing industries, and will soon have big impacts on our health, jobs, entertainment, and entire lives. They are Artificial Intelligence, and Big Data. Of course, these have already had big effects in certain applications, but I expect that they will become even more important as they improve. My colleague Dr. James Short is putting together a conference called Data West at the San Diego Supercomputer Center, and I came up with a list of fears that might disrupt their emergence.

1) If we continue to learn that ALL large data repositories will be hacked from time to time (Experian; National Security Agency), what blowback will that create against data collection? Perhaps none in the US, but in some other countries, it will cause less willingness to allow companies to collect consumer data.

2) Consensual reality is unraveling, mainly as a result of deliberate, sophisticated, distributed, attacks. That should concern all of us as citizens. Should it also worry us as data users, or will chaos in public venues not leak over into formal data? For example, if information portals (YouTube, Facebook, etc.) are forced to take a more active role in censoring content, will advertisers care? Again, Europe may be very different. We can presume that any countermeasures will only be partly effective – the problem probably does not have a good technical solution.

3) Malware, extortion, etc. aimed at companies. Will this “poison the well” in general?

4) Malware, extortion, doxing, etc. aimed at Internet of Things users, such as household thermostats, security cameras, cars. Will this cause a backlash against sellers of these systems, or will people accept it as the “new normal.” So far, people have seemed willing to bet that it won’t affect them personally, but will that change. For example, what will happen when auto accidents are caused by deliberate but unknown parties who advertise their success? When someone records all conversations within reach of the Alexa box in the living room?

Each of these scenarios has at least a 20% chance of becoming common. At a minimum, they will require more spending on defenses. Will any become large enough to suppress entire applications of these new technologies?

I have not said anything about employment and income distribution. They may change for the worse over the next 20 years, but the causes and solutions won’t be simple, and I doubt that political pressure will become strong enough to alter technology evolution.

Reality versus belief, and the American right

Warning: this post is entirely opinion about American politics.

Bret Stephens had an interesting op-ed in the NY Times recently. On first reading, it was great. Then I went through the comments, and realized it was quite one-sided. (He is a conservative, over from the WS Journal.) So I wrote the following letter to the editor.

In his column of Sept. 24 Mr Stephens sharp eye noticed, and sharp tongue castigated, only the left’s fundamental error in today’s discussions: judging arguments based on the speaker’s identity. But even more destructive is the fundamental error found primarily on the right: judging arguments based on the desire to believe them. That Congressman R believes something, no matter how strongly, does not make it true, nor a valid basis for setting policy.

I  am at a university that emphasizes science and engineering, and teaches little about Mr. Stephens’ Great Books. But we  teach our students that objective reality exists, and that it matters.  We base our arguments on empirical evidence. And if evidence is insufficient, we look for more.

Here are a few examples of facts that are somehow viewed as controversial: making contraception and information more available to teenagers reduces unwanted pregnancies, and abortions. (See Colorado for a large-scale proof.) Vaccinations reduce disease. Cutting income taxes of the rich will do little to stimulate the economy when the economy is near full employment. Pumping gases into the atmosphere creates a “greenhouse effect.” There is room to disagree about what actions to take as a result of these facts, but not about the facts themselves.

I have elsewhere argued that America (and other parts of the world) are retreating from Reason back to Faith, reversing the Enlightenment of the 1600s. If this continues, the consequences for our country will be dire. But that is a longer discussion.

Photovoltaics in Mission Bay neighborhood = 30% wasted

TL;DR In Southern California should put PV on houses and buildings that are far from the coast, because coastal areas are cloudy much of the summer. But the actual pattern is the opposite. I estimate a 30% magnitude of loss. Even my employer, UCSD, has engaged in this foolishness in order to appear trendy.

The bumpiness of this graph shows the effects of coastal weather in August.

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