Thought-provoking article on AI

The New York times (who else? – they really seem to be all over this machine intelligence stuff lately) has published an Op-Ed by Jaron Lanier, a research scientist at Microsoft.  The article twists the typical conversation about AI on its head, saying that one of the effects of AI is that people are turning more machine-like rather than machines turning more human-like, and in the process we are essentially losing our soul.

Pretty heavy stuff, for sure.

I’ll focus on one interesting snippet in the article:

We must instead take responsibility for every task undertaken by a machine and double check every conclusion offered by an algorithm, just as we always look both ways when crossing an intersection, even though the light has turned green.

This passage kind of struck a personal chord for me. In my former job, we worked on a system called TCAS, which is a collision avoidance system mandated by law to be installed on all aircraft around the world of a certain size. Certainly, all the commercial passenger jets in the United States have this system installed.

This system could easily be called artificial intelligence – it uses sensors to detect approaching aircraft and issues commands, based on decisions made by algorithms, to the human pilot who would nominally be expected to execute the commands faithfully. The system was developed because of an act of Congress after a series of tragic mid-air collisions in the 50′s, 60′s and 70′s. The system “went live” in 1992, I believe, and there are international bodies containing very dedicated and smart people continuing to work on upgrading it since then.

Where it gets interesting, and related to the author’s quote above, is where the human fits in with this system. For example, pilots are supposed to always follow TCAS’ commands, unless they have overriding visual evidence to support a different decision. The reason is that multiple TCAS systems will actually coordinate actions between the two planes if necessary to separate them.

Now, where it gets really interesting (and tragic) is when despite the rules, one or both pilots choose to take actions opposite to what TCAS tells them to do, as they did in Uberlingen Germany in 2002. In this case, one of the pilots obeyed the commands of the controller, and as a result, there was a mid-air collision and 71 people died.

While there are indeed technical solutions (CP112E) in this case – which I personally worked on verifying – it brings up a case where human judgement was faulty and the algorithm was correct, and the result of the human “double check” caused harm.

In general, I am actually in the author’s camp that handing over your free will to a machine should at least give you pause, and I don’t dispute that we are slowly becoming more machine-like. I support all the creative/independent thinkers out there, because I think it’s getting tougher for people to trust your judgement in the presence of the Social Network.

But I also believe that in some situations, like in Uberlingen, it’s not always a bad thing to accept a machine’s advice. Unquestionably, the human element introduces “noise” which waters down the effectiveness of algorithms such as TCAS.  I predict it will be the great ethical and legal struggle of my generation to find out where to draw the line.  While it would be great if it were always an individual choice (such as shutting down your Facebook account), I can see examples similar to Uberlingen coming down the line in other life or death situations like in medicine and for safety systems in other contexts where something will have to give.

I seem to be more optimistic than the author, however, on the macro level. I think the slow revolution of society being caused by the AI all around us is causing us to think about our lives and society more logically which will ultimately lead to more social justice.

Either that or you’ll get the computer from Wargames, not sure.

Tic-tac-toe anyone? The only winning move is not to play...

Announcement – New LGO EECS track: Information and Decision Systems

The Information and Decision Systems (IDS) track is designed for LGO students in EECS who want to both explore and develop practical skills in how to apply the latest algorithms and mathematical analysis in real operational settings.

The goal of the track is to make LGO the premier training program for leaders who will use advanced data analysis to make smarter operational decisions. The track includes five courses in four areas: 2 courses in tools/theory, 1 course in design, 1 course in communication and 1 course in an engineering elective specific to an application area.

We have a great adviser in Professor Patrick Jaillet, who is associated with LIDS and is also the new co-director of the Operations Research Center at Sloan.

In the coming months, we will be preparing track materials for the LGO Open House and fleshing out how to make this track an active group in the LGO community, much like the sustainability program in ESD.  Shoot me an email if you are interested or have ideas…

Plug for MIT Lincoln Laboratory (“The Lab”)

 

 

As cool as it looks

As cool as it looks

For the past two years I have worked at MIT Lincoln Laboratory, or the Lab for short. Not many people outside of the research circles know about this place, and in fact I only stumbled upon it in my job search because I went to a job fair for high tech companies and got some literature.  In fact, the wikipedia page on the Lab is comically short considering the amount of research that has been conducted there for the past 50+ years – while the Lab didn’t invent radar, it probably perfected it. However, because most of this research is classified for national security, 95% of the amazing work by Lab scientists goes unpublished.  When I was looking around for information on the Lab, I could hardly find any online, so hopefully somebody may stumble upon this page when they are thinking about working there. 

While at the Lab, I worked for the Surveillance Systems group, Group 42. When I got to the Lab, the group was called the Air Traffic Control and Surveillance Systems Group, and about half of the group’s research is sponsored by the FAA. Most of my work centered around the TCAS collision avoidance system, which is mandated by Congress to be installed on every commercial passenger aircraft above a certain size.

TCAS vertical speed indicator (displayed in cockpit)

TCAS vertical speed indicator (displayed in cockpit)

I also worked on new collision avoidance systems for UAVs (Unmanned Air Vehicles). My major project was developing airspace encounter models for generating random, realistic encounters so that these systems can be tested in simulation. Over the course of developing these models, I learned a great deal about Bayesian networks, Monte Carlo methods, importance sampling, radar (note: the giant radar ALTAIR in that link is operated by Lincoln for missile defense in the Marshall Islands), flight dynamics, and especially air traffic control. It was a fascinating project, and only one of many fascinating projects that I was involved in (I will probably blog about my thoughts on ATC at some point in the future).

 

Global Hawk, one of the platforms we worked with.

Global Hawk, one of the platforms we worked with.

I’ve worked with some amazingly smart and capable people who I now consider my friends.  In particular Mykel Kochenderfer and Jim Kuchar have been my mentors, among many others who don’t have personal websites. Over half of the Lab employees have PhDs, most from MIT and other top schools, and the sheer brain power there is kind of awesome. People also work at the Lab for the love of their research, and that definately comes through as well.

I will be leaving the Lab in a couple months because I accepted an offer to be a LGO fellow at MIT. However, my work there has been very intellectually satisfying, and it has served to focus my future academic interests. For instance, I will recieve a MS in Computer Science, largely because my work at the Lab has piqued my interest in AI and machine learning. In particular, I hope to research how these principles can be applied to improve the efficiency and operation of manufacturing companies.  I would say that the Lab is an excellent place to work if you are interested in doing cutting edge research, are intellectually curious and smart, and enjoy tackling difficult problems in the area of national defense, homeland security or the FAA.