Believe the AI hype?

Will 2019 be the year of artificial intelligence?

The Guardian

Don't believe the hype: the media are unwittingly selling us an AI fantasy | John Naughton

Artificial intelligence (AI) is a term that is now widely used (and abused), loosely defined and mostly misunderstood. Much the same might be said of, say, quantum physics. But there is one important difference, for whereas quantum phenomena are not likely to have much of a direct impact on the lives of most people, one particular manifestation of AI – machine-learning – is already having a measurable impact on most of us.

The tech giants that own and control the technology have plans to exponentially increase that impact and to that end have crafted a distinctive narrative. Crudely summarised, it goes like this: “While there may be odd glitches and the occasional regrettable downside on the way to a glorious future, on balance AI will be good for humanity. Oh – and by the way – its progress is unstoppable, so don’t worry your silly little heads fretting about it because we take ethics very seriously.”

Read Full Article
Download Perspecs

Alan Turing and the origins of artificial intelligence

By Daniel J. McLaughlin

On February 20, 1947, Alan Turing predicted the rise of artificial intelligence. The term "artificial intelligence" had not been coined during Turing's lifetime - John McCarthy would come up with it in 1956, two years after the Enigma codebreaker's tragic death. He did, however, lay out the fundamentals of what we know as artificial intelligence today.

Speaking to the London Mathematical Society, Turing declared that "what we want is a machine that can learn from experience". During his speech, he debated whether machine learning will help humans to perform better at their jobs (augmentation) or destroy the jobs (automation).

As well as showing a considerable amount of foresight 60 years ago, the mathematician concluded that the machines should not be more intelligent than humans. He said: "One must therefore not expect a machine to do a very great deal of building up of instruction tables on its own.

"No man adds very much to the body of knowledge, why should we expect more of a machine?

"Putting the same point differently, the machine must be allowed to have contact with human beings in order that it may adapt itself to their standards."

Three years later, Alan Turing posed a question he deemed "absurd": can machines think?

In his 1950 paper, Computing Machinery and Intelligence, he first attempted to define thinking before deciding it was too difficult. Instead, he devised the Imitation Game: a test to find out whether a computer could trick a human into thinking it is a fellow human.

This method, known as the Turing Test, is used today. The first version of the test involved no computer intelligence whatsoever. Instead, Turing explained that there were three rooms, each connected via a computer screen and a keyboard. In one room is a man, the next contains a woman, and in the third is a human judge. The judge is there to determine through the computer which one is the man. The man will attempt to offer evidence of his gender, whilst the woman attempts to trick the judge, and hope they will identify her as the man.

Turing later modified the test. Instead of a man and a woman, there was a human of either gender and a computer, whose job it is to convince the human judge at one side of a computer screen that they are human.

According to the Washington Post, for a computer to pass the test, it must trick 30 per cent of the human interrogators who converse with the computer for five minutes in a text conversation.

When Alan Turing delivered his speech to the London Mathematical Society, and wrote his paper proposing the test, he simply posed hypotheses about artificial intelligence. Over 60 years later, the theories are becoming a reality.

Download Perspecs

Mobile, social, and cloud will boost artificial intelligence

The Consumer Electronic Show (CES) was full of artificial intelligence (AI) agents of change this past week. Amazon noted that 28,000 products are now partnered with Alexa, up from 4,000 this time last year. Distributing more content is a key focus of AI home devices, and Amazon, Google, Microsoft, and Samsung were all showcasing the AI-enabled life-enhancing features of their digital assistants. For this trend to continue, we need to embrace the policy challenges that AI brings to data collection and privacy.

The explosion in AI products has been made possible by today’s network speeds. High speed networks enable applications to take advantage of real time information flow to deliver media, communications, and information such as live GPS data, then feed it back into cloud computing software to curate and manage the data more efficiently and accurately than ever before. Smartphone and voice assisted platforms are powering the app economy and these applications need the efficiency brought on by more data aggregation. AI has become an easily accessible technology for both large corporations and individual users, and society has become unknowingly dependent on AI and machine learning to make sense of the flood of information available.

Read Full Article
Download Perspecs