Kill the baby or the grandma?

What used to be an arcane problem in philosophy and ethics, The Trolley Problem, has been taking center stage in the discussions about the way autonomous vehicles should behave in the case of an accident. As reported previously in this blog, a website created by MIT researchers, The Moral Machine, gave everyone the opportunity to confront him or herself with the dilemmas that an autonomous car may have to face when deciding what action to take in the presence of an unavoidable accident.

The site became so popular that it was possible to gather more than 40 million decisions, from people in 233 countries and territories. The analysis of this massive amount of data was just published in an article in the journal Nature. In the site, you are faced with a simple choice. Drive forward, possibly killing some pedestrians or vehicle occupants, or swerve left, killing a different group of people. From the choices made by millions of persons, it is possible to derive some general rules of how ethics commands people to act, when faced with the difficult choice of who to kill and who to spare.

The results show some clear choices, but also that some decisions vary strongly with the culture of the person in charge. In general, people decide to protect babies, youngsters and pregnant women, as well as doctors (!). At the bottom of the preference scale are old people, animals and criminals. 

Images: from the original article in Nature.

Hello World: how to be human in the age of the machine

Computers, algorithms, and data are controlling our lives, powering our economy and changing our world. Unlike a few decades ago, the larger companies on the planet deal mostly with data manipulation, processed by powerful algorithms that help us decide what we buy, which songs we like, where we go and how we get there. More and more, we are becoming unwitty slaves to these algorithms, which are with us all the time, running on cell phones, computers, servers, and smart devices. And yet, few people understand what an algorithm is, what artificial intelligence really means, or what machine learning can do.

Hannah Fry’s new book opens a window on this world of algorithms and on the ways they are changing our lives and societies. Despite its name, this book is not about programming nor is it about programs. The book is about algorithms, and the ways they are being used in the most diverse areas, to process data and obtain results that are of economic or societal value.

While leading us through the many different areas where algorithms are used these days, Fry passes on her own views about the benefits they bring but also about the threats they carry with them. The book starts by addressing the issue of whether we, humans, are handling too much power to algorithms and machines. This has not to do with the fear of intelligent machines taking over the world, the fear that a superintelligence will rule us against our will. On the contrary, the worry is that algorithms that are effective but not that intelligent will be trusted to take decisions on our behalf; that our privacy is being endangered by our willingness to provide personal data to companies and agencies; that sub-optimal algorithms working on insufficient data may bring upon us serious unintended consequences.

As Fry describes, trusting algorithms to run our lives is made all the more dangerous by the fact that each one of us is handing over huge amounts of personal data to big companies and government agencies, which can use them to infer information that many of us would rather keep private. Even data that we deem most innocent, like what we shop at the grocery, is valuable and can be used to extract valuable and, sometimes, surprising information. You will learn, for instance, that pregnant women, on their second trimester, are more likely to buy moisturizer, effectively signaling the data analysts at the stores that a baby is due in a few months. The book is filled with interesting, sometimes fascinating, descriptions of cases like these, where specific characteristics on the data can be used, by algorithms, to infer valuable information.

Several chapters are dedicated to a number of different areas where data processing and algorithmic analysis have been extensively applied. Fry describes how algorithms are currently being used in areas as diverse as justice, transportation, medicine, and crime prevention. She explains and analyses how algorithms can be used to drive cars, influence elections, diagnose cancers, make decisions on parole cases and rulings in courts, guess where crimes will be committed, recognize criminals in surveillance videos, predict the risk of Alzheimer from early age linguistic ability, and many other important and realistic applications of data analysis. Most of these algorithms use what we now call artificial intelligence and machine learning but it is clear that, to the author, these techniques are just toolboxes for algorithm designers. The many examples included in these chapters are, in themselves, very interesting and, in some cases, riveting. However, what is most important is the way the author uses these examples to make what I feel is the central point of the book: using an algorithm implies a tradeoff and every application brings with it benefits and risks, which have to be weighted. If we use face recognition algorithms to spot criminals, we have to accept the risk of an algorithm sending an innocent person to jail. If we police more the locations where crimes are more likely to take place, people on those areas may feel they are treated unfairly. If we use social data to target sale campaigns, then it can also be used to market political candidates and manipulate elections. The list of tradeoffs goes on and on and every one of them is complex.

As every engineer knows, there is no such thing as 100% reliability or 100% precision. Every system that is designed to perform a specific task will have a given probability of failing at it, however small. All algorithms that aim at identifying some specific targets will make mistakes. They will falsely classify some non-target cases as targets (false positives) and will miss some real targets (false negatives). An autonomous car may be safer than a normal car with a human driver but will, in some rare cases, cause accidents that would not have happened, otherwise. How many spurious accidents are we willing to tolerate, in order to make roads safer to everyone? These are difficult questions and this book does a good job at reminding us that technology will not make those choices for us. It is our responsibility to make sure that we, as a society, assess and evaluate clearly the benefits and risks of each and every application of algorithms, in order to make the overall result be positive for the world.

The final chapter addresses a different and subtler point, which can be framed in the same terms that Ada Lovelace put it, more than 150 years ago: can computers originate new things, can they be truly creative? Fry does not try to find a final answer to this conundrum, but she provides interesting data on the subject, for the reader to decide by him- or herself. By analyzing the patterns of the music written by a composer, algorithms can create new pieces that, in many cases, will fool the majority of the people and even many experts. Does this mean that computers can produce novel art? And, if so, is it good art? The answer is made the more difficult by the fact that there are no objective measures for the quality of works of art. Many experiences, some of them described in this chapter, show clearly that the beauty is, in many cases, in the eye of the beholder. Computer produced art is good enough to be treated like the real thing, at least when the origin of the work is not known. But many people will argue that copying someone else’s style is not really creating art. Others will disagree. Nonetheless, this final chapter provides an interesting introduction to the problem of computer creativity and the interested reader can pick on some of the leads provided by the book to investigate the issue further.

Overall, Hello World is definitely worth reading, for those interested in the ways computers and algorithms are changing our lives.

Note: this is an edited version of the full review that appeared in Nature Electronics.