Understanding artificial intelligence

European Parliament - EPRS Policy podcasts

European Parliament Webmaster

Non-profit, Government & Organizations

4.8 • 13 Ratings

🗓️ 12 January 2018

⏱️ 7 minutes

🔗️ Recording | iTunes | RSS

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Summary

Artificial intelligence (AI) systems already permeate daily life: they drive cars, decide on mortgage applications, translate texts, create artworks, play games, and intervene in conflict zones. The briefing explores the roots of the AI revolution that emerged from the combination of machine learning techniques and 'big data'. It also explores the current limitations of these systems: they are perform single tasks, can be biased and are opaque in their decision making. The development of AI systems requires adaptation of legal frameworks on the collection, use and storage of data. But more importantly, the key issue remains the level of autonomy given to AI systems to make decisions that could be life-changing. If the threat of a 'superintelligence' able to self-improve and dominate humans remains remains unrealistic, AI systems are expected to impact society, especially the job market, and could increase inequalities.

Source: © European Union - EP

Transcript

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0:00.0	You're listening to the European Parliamentary Research Service podcast on artificial intelligence.
0:09.0	From replicant humans to machine-controlled societies and sophisticated virtual environments,
0:16.0	artificial intelligence has been a recurrent theme in science fiction.
0:20.0	But with real-world advances in machine learning and deep learning, the gap between reality
0:24.9	and fiction is narrowing.
0:26.5	But how much?
0:27.6	Stay with us.
0:31.4	Even if the notion of thinking machines was already being explored by great minds, such
0:35.9	as the English mathematician and World War II
0:38.5	Codebreaker Alan Turing since the 1930s, the term artificial intelligence was only coined in
0:44.4	1956 by the American computer scientist John McCarthy.
0:48.7	One year later in 1957, Nobel Prize winner Herbert Simon predicted that computers would
0:53.9	beat humans at chess within 10 years.
0:56.6	It took 40, but in 1997, IBM's supercomputer Deep Blue made the winning move that defeated chess legend Gary Kasparov,
1:05.3	sparking renewed interest in the possibilities of artificial intelligence. But what do we understand by artificial intelligence?
1:11.9	It is broadly understood as the science of making computers do things that require a certain
1:17.0	degree of intelligence when performed by humans, such as reasoning, learning, solving problems,
1:22.9	or understanding language. The idea that it should be possible to deconstruct human intelligent behavior into
1:29.0	a succession of logical steps and rules, which could be transcribed into algorithms and programmed
1:34.2	into machines, led to the development of symbolic artificial intelligence in the 1960s.
1:40.0	But translating knowledge into symbols and defining all the rules necessary for a machine to be
1:45.0	able to interpret those symbols and act like a human proved to be an overwhelming task,
	...

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