Hawaii alert: it could have been worse

This weekend, residents of Hawaii woke up to an unpleasant text message from the authorities informing them of an inbound ballistic missile. As we now know, it was a false alarm although the 38 minutes that it took to get that news out to the folks who had received the alert were presumably anxious ones. The false alert was even more concerning than it might have been because of the already heightened tensions with North Korea. That country has, in fact, been launching nuclear capable ballistic missiles into the Pacific Ocean as part of its nuclear program. Initial root cause analysis has revealed that the Hawaiian alert problem was caused by the user interface—the test warning tab was adjacent to the warning tab on the pull-down menu, a trivial mistake.

What happened in Hawaii is only one of many such events, albeit scarier. When Air France Flight 447 went down in South Atlantic, the aircraft was flown intact and with engines running into the water because the pilots became confused as to the airspeed due to conflicting messages from its computer systems. A recent fatal Tesla accident occurred when during self-driving mode when the car’s computer became situationally unaware of its immediate environment. Increasingly, we are dependent upon the human-machine interface for our safety and well being. Yet, as with HAL in Kubrick’s 2001 A Space Odyssey, every contingency cannot be programmed for.

It doesn’t take much imagination to surmise that North Korea’s military command was made aware of the Hawaiian nuclear alert shortly after it was received by millions across Oahu and the rest of the islands that make up the State. Given the paranoia of the regime, it’s relatively easy to see how they might have interpreted the alert, not as an error, but as a US false flag operation to justify a premptive strike on the regime. In such a situation, where the North Koreans believed that they must “use or loose”, they well might have attacked with catastrophic results to all.

With more of our technologies become AI-enabled, the potential for common mishaps will go down (e.g. self-driving cars will get in fewer fender-benders) yet the potential for long-tail “black swan” events can’t be discounted. Returning to the events in Hawaii, it has always been too easy to lauch nuclear weapons. In the U.S. there is a single-point of potential failure—the President. That individual alone has the authority to cause a launch without any checks or balances from Congress. With AI increasingly entering the picture, the information stream that might lead to a failed decision, flows through the black box of machine learning and opaque algorithms. Where the consequences are high, it is high time that neither machine nor human can easily commit to catastrophic error by means of trivial mistake.

Tracking investments in graduate education

During my time leading the Biological Sciences Directorate at NSF, I learned that the agency spends around a billion dollars a year on graduate education—the training that is required after the undergraduate degree to turn an aspiring scientist into a true discoverer. Of that money, roughly 15% is spent on NSF’s flagship graduate research fellowships—a fantastic program that’s been around since the 1950’s and has played a central role in the early careers of many of the US science superstars. These are folks who have gone on to win Nobel prizes and the like. Winning these fellowships involves an intense competition of ideas and is peer-reviewed by the science community. I’m pleased that NSF tracks the career trajectory of these trainees pretty carefully. There is hard evidence that the graduate research fellowship program works.

Another 5% of the total is spent on trainee grants—the current version of these are the National Research Traineeships. These are training awards that go to universities which then award the support to graduate students that they select. I was trained under such a program (although it was NIH funded) when I was at the University of Michigan training in neuroscience. These are excellent funding programs and once again those folks who are supported in this way are tracked pretty carefully (I still get contacted regularly by the NIH asking what I’m up to).

But the vast majority, 75%, of what the NSF invests in graduate education is untracked. These embedded in the dollars that go to research grants of scientists at US universities who then hire graduate student research assistants to actually do the work. We don’t know what happens to these trainees. There simply is no easy way at getting at the data.

In strikes me as unwise to make such a large investment without getting feedback on how things are going. In particular, I am concerned that those graduate students are being inadequately mentored in some pretty substantive ways. For example, I fear that they are too often treated as an extra pair of hands rather than a future professional colleague. Time spent teaching these students about career options or how to effectively teach undergraduate students is time away from the laboratory bench.

There are ways of tracking such students. One such mechanism is the orcid id system. There are others. If all students supported by the NSF were required to be registered in such a system, then it would be possible to track their career easily (as long as they stayed in science). But success on that front requires one other thing: that journal publishers and data repository sites require that a person’s id be attached as meta-data to every single piece of scientific data from the results of a single bench top experiment or a field observation all the way to a finished journal article.

This is not impossible. I think it is important to move this direction because it will allow for evidence based decisions about how to optimize NSF’s graduate student support in the future.

About that photo…

The one at the top of this page. I took that photo on the edge of the Arctic Ocean in Barrow Alaska. In the foreground is a whale skull. It’s a stark scene and in a sense a perfect visual metaphor for the uncertain times we live in. You’ll notice a complete absence of sea ice. With a good dry suit, I could have gone surfing. This was not always the case. While Climate.gov is still live, you can see quantitatively how drastically the environment has changed in Barrow here.

Much of the tundra in Alaska is permafrost. That includes communities such as Barrow. And that permafrost is now rapidly thawing. So Barrow’s future is quite uncertain. Look at my photo one more time. Real enough, right?

Jim Olds returns from NSF

I am back at George Mason University after 3 years of heading up the Biological Sciences Directorate at the U.S. National Science Foundation. For those of you who have not followed my career, this was after 16 years heading up the Krasnow Institute for Advanced Study at George Mason and Chairing the Molecular Neuroscience Department. These days find me at the Schar School of Public Policy and Government where I am University Professor of Neuroscience and Public Policy.

 

 

Cass Sunstein interviewed on conspiracy theory thinking and political partisanship…

From Vox, interview is here. I’ve blogged on this topic previously here. Not much to add except the notion of epistomological closure seems to be important. That is hanging out with like-minded conspiracy theorists seems to harden belief in the conspiracy theory.

The other interesting tidbit from the Cass Sunstein video is the notion that when the authorities deny a conspiracy theory, that also acts to harden belief in the believers.

Commencement 2014

Provost and Deans, George Mason University 2014

My colleagues and I got together for our annual informal photo just prior to commencement this morning. These are wonderful folks to work with. Today’s ceremony marks the end of my 16th year in this position. It’s been an incredibly fulfilling job. Happy Summer!