Group 12 – Microsoft’s digital strategy
22
October
2017
October
2017
September
2017
Almost a century ago, in 1930, the famous economist John Maynard Keynes made a prediction that technology would make us so productive that a major problem we will face will be “how to occupy the leisure which science and compound interest will have won for him, wisely and agreeably and well?” (Keynes, 1933).
Nowadays, with the rise of new technologies, machines, and artificial intelligences, many people are starting to thing that he was right and that AI-powered robots are going to steal their jobs. But is that really true? Will AI really make us all unemployed?
Of course it is certainly true that the always-improving technologies will render several human jobs redundant and unnecessary. For instance, the United Kingdoms have announced that, by the end of the year, they would release a “fleet of driverless lories” to be trialled on the UK’s motorways (Swinford and Krol, 2017). Autonomous car technology has already successfully being tested in other European countries, and we can expect it to render many jobs (e.g. truck and taxi drivers) irrelevant in the future. Similarly, robots and AI have a non-negligible impact on many other industries, especially in production processes.
However, even if automation will undoubtedly steal away many of our jobs, it is not really a problem. In fact, it has already happened before. As Kurzeil, director of engineering at Google Ray, said during his interview with Fortune, around 1900, most people worked in farms and factories, but most of these jobs don’t exist anymore nowadays (Lev-ram, 2017). Nevertheless, most people are still employed, because for each job eliminated, new ones were created. The same is likely to happen in our technological era; it is just too soon to see what the career landscape will look like in 5 or 10 years, which can be quite unsettling.
So does that mean that there is no need to worry about the future, and that everyone will still be able to easily find a job? I believe not. Indeed, as technology evolves and reshape or take over human tasks, the knowledge needed to perform these modified or completely new jobs change as well. The question is, will people have the necessary to perform these new tasks? Whereas us Bimmers are lucky enough to learn about subjects relevant for the future (e.g. Machine learning, Big data), I don’t believe that it is the case for all students, and even less for currently employed people.
I will finish by asking you what you think we could do to address this skill gap? What could we do to ensure that current employees have an easier transition from one occupation to another? Let me in the comments!
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September
2017
A few years ago, I watched Person of Interest – a TV series in which Artificial Intelligence (AI) is used to analyse data from cameras, computers, and other electronic devices, making it possible to predict and prevent crimes before they even happen. At the time, I never thought something like that was possible but well, that has changed. Even though AI technologies available today are nowhere as sophisticated as in the show, experts affirm that there have been some serious progress in that direction.
According to Dr. Simon See – director for NVDIA AI technology center – “AI can predict the probability of crime in a location by detecting anomalies and faces”. This is exactly what China is aiming to do. Cloud Walk, a company located in Guangzhou Tianhe Software Park, combines its facial recognition software and big data analysis tools to track people’s location and behaviour in order to assess the odds of them committing a crime. Suspicious behaviours, such as frequent visits to gun shops or transportation centres (a good target location for terrorists), are flagged, and a warning is forwarded to the local police. The law enforcement forces can then intervene before the crime even happens.
In addition, in Durham, England, the law enforcement forces are making use of HART – an AI system developed by a Professor of Cambridge University – to help them determine whether a suspect should be released or keep in custody. HART uses the police’s database to forecast the risk of a suspect re-offending by putting them in either a low, moderate or high-risk category. The police can then decide on the appropriate course of action based on the ranking. Although the system is not yet ready to be deployed on a large scale, the tests conducted in Durham are quite encouraging as only 2% of low-risk suspects went on to commit a serious offense. Similarly, in the US, law courts and correction departments are making use of AI to help them pass judgement. Similarly to HART, the system determines the likelihood of the defendant committing another offense or whether he’s likely to appear to his court date. Based on the output, the court can then make decisions about bail, sentencing, and parole.
After reading a few articles to write the present post, I immediately thought that using AI to reduce criminal offenses seemed to be an amazing idea to – reduced criminality, terrorist attacks prevented, less “detective work” for the law enforcement forces, what else could we want? However, after further considerations, I believe that even if AI might be able to prevent some crimes in the ways mentioned previously, it also presents several issues.
First, whoever does the design and coding brings his own beliefs, biases, misunderstandings, and, most crucially, prejudices to the party. As long as this issue is not fixed, should we really trust a man’s freedom with a machine that might contain hidden biases rather than a jury composed of random people from different backgrounds?
Second, it is important not to forget that the law enforcement forces are not the only ones making use of IT, criminals also do. Thus, although AI might prove useful in reducing criminality, it also poses new threats to security, and as long as we don’t find ways to counter these, I wouldn’t trust my life to an auto-driven car or the likes.
And you, what do you think about AI as a way to reduce criminality & passing judgements? Let me know in the comments.
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