What do engineers assume about users’ ability to specify what they want?

I came across the following wonderful gems of tech history quotes in one of my recent readings:

The relational model is a particular suitable structure for the truly casual user (i.e. a non-technical person who merely wishes to interrogate the database, for example a housewife who wants to make enquiries about this week’s best buys at the supermarket).

In the not too distant future the majority of computer users will probably be at this level.

(Date and Codd 1975; 95)

Casual users, especially if they were managers might want to ask a database questions that had never been asked before and had not been foreseen by any programmer.

(Gugerli 2007)

As I was reading these, it occurred to me that many in my own area of robotics also often think in the same way. What would the proper abstractions look like in emerging areas such as robotics, mirroring the advances that have happened in the software space (e.g., contrast the above vision vs. Apple’s offerings today)? Our typical iPad-toting end user is going to speak neither SQL nor ROS, yet the goal of robotics is to let them flexibly and naturally program the machine – how can that actually be achieved?


  1. C.J. Date, E.F. Codd, The relational and network approaches: Comparison of the application programming interfaces, Proc. SIGFIDET (now SIGMOD) 1974.
  2. D Gugerli, Die Welt als Datenbank. Zur Relation von Softwareentwicklung, Abfragetechnik und Deutungsautonomie, Daten, Zurich, Berlin: Diaphanes, 2007.

Where could machines replace humans?

This is the primary question shaping much of the public debate and discourse around the development of autonomous systems technologies, robots being the most visible and eye catching example – occasionally quite scary when you see them being used, e.g., as carriers of weapons and bombs. As a roboticist who is often deeply ensconced in the technical side of developing capabilities, I find most public articles in the popular media to be ill-informed and hyperbolic. So, I was pleasantly surprised to read this McKinsey report. This is not quite popular media, but in the past I have found even some of these consulting company reports to be formulaic. The key point being made by the authors is that just because something can be automated does not mean it should, or that it will. In reality, a variety of different factors, including economic and social will shape the path of these technologies – something all of us should pragmatically consider.

This key point is summarised in the following excerpt:

Technical feasibility is a necessary precondition for automation, but not a complete predictor that an activity will be automated. A second factor to consider is the cost of developing and deploying both the hardware and the software for automation. The cost of labor and related supply-and-demand dynamics represent a third factor: if workers are in abundant supply and significantly less expensive than automation, this could be a decisive argument against it. A fourth factor to consider is the benefits beyond labor substitution, including higher levels of output, better quality, and fewer errors. These are often larger than those of reducing labor costs. Regulatory and social-acceptance issues, such as the degree to which machines are acceptable in any particular setting, must also be weighed. A robot may, in theory, be able to replace some of the functions of a nurse, for example. But for now, the prospect that this might actually happen in a highly visible way could prove unpalatable for many patients, who expect human contact. The potential for automation to take hold in a sector or occupation reflects a subtle interplay between these factors and the trade-offs among them.

Rule-bound robots and reckless humans

I found this article, and the associated discussions about what exactly is needed for a useful level of autonomy to be really interesting: http://nyti.ms/1LRy9MF.

A point that immediately stands out is this: “Researchers in the fledgling field of autonomous vehicles say that one of the biggest challenges facing automated cars is blending them into a world in which humans don’t behave by the book.” Roboticists should of course realise that this is the real and complete problem – we can’t just complain about problem humans who do not ‘behave by the book’ – that is exactly the wrong way to approach the design of a usable product! Instead, we need to focus on how to make the autonomous system capable enough to learn and reason about the world – including other agents – despite their idiosyncrasies and irrationality! This really is the difference between the rote precision of old and genuinely robust autonomy of the future.

In our own small way, we have been approaching such issues with projects such as the following:

If you are a UK student looking to work on a PhD project in this area, look into this studentship opening: http://www.edinburgh-robotics.org/vacancy/studentship/571.

Robot gadgets

I like this article in the New York Times today, asking about the status of truly pervasive robots.

An important point that we researchers don’t like talking about is:

The most advanced robots remain exotic workhorses like NASA’s Mars Curiosity Rover, which cost $2.5 billion, and the LS3, a doglike robot being developed for the U.S. military that can carry a 400-pound, or 180-kilogram load more than 20 miles, or about 30 kilometers. The mechanical beast of burden, whose price is not public, is being made by a consortium led by Boston Dynamics. In Menlo Park, California, engineers at Willow Garage, a robotics firm, are selling the two-armed, 5-foot-4 inch (1.63-meter) rolling robot called the PR2 for $400,000.

A video on Willow Garage’s Web site shows the PR2 fetching beer from a refrigerator, which while an engineering and programming feat, is an expensive way to get beer.

In a recent interview I saw on Bloomberg TV, Colin Angle, co-founder of iRobot, discussed what it took for him to make one such product, the Roomba, pervasive. The transition, as he put it, was the one from talking about advances in robotics to thinking like a vacuum cleaner salesman and making sure the robotics technology really does deliver on the applications front.

Now, most of us didn’t become robotics researchers to think about vacuum cleaner sales but it does seem to me that if we are really serious about robots ‘everywhere’, we must ask what the broader class of applications are and what is preventing those. These issues are likely to be quite different from that of building an even more bigger badder robot – requiring a whole other kind of innovation and techniques. Perhaps we should remember how areas like wireless communications become even more interesting to academics precisely because of the focus on actually making these devices part of our lives (it is literally the last piece of technology I interact with before I go to sleep and the first piece of technology I wake up to – when can we say that about a robot?!).