Technology is changing so fast that it is sometimes, in all the excitement, it is easy to be carried away by the hype. Developments in artificial intelligence (AI) are a case in point.
For example, a chess-playing programme called AlphaZero, developed by the Alphabet-owned (Google’s parent) AI research company DeepMind, has been making very important advances. AlphaZero’s bravado on the chess board has led to reports in the media about “human-like intuition and creativity” and watershed moments in history.
The story is that AlphaZero has developed a new style of playing chess which is much closer to human improvisation than traditional computer chess. That is because AlphaZero learns from its past successes and mistakes, rather than calculating millions of possible permutations as it plays. For the record, according to Wikipedia, AlphaZero searches 80,000 positions per second in chess, compared to 70 million for the Stockfish chess engine.
AlphaZero uses (deep) neural network technology — sometimes called deep learning — made possible over the past decade by notable improvements in machine learning. As computing power has increased, deep neural networks have made machines capable of performing tasks in a way that would not have been possible using traditional programming techniques.
This has transformed technologies such as computer vision and natural language processing (NLP), which are nowadays being deployed at a massive scale in many different products and services. Manufacturing, healthcare and finance are just some of the sectors that use deep learning to uncover new patterns, make predictions and to guide decision making.
It is a fantastic piece of technology, but there is nothing human-like about AlphaZero’s chess playing exploits. The programme is uniquely focused on the task of playing chess and has only the ability to recognize patterns in moves and positions and to act accordingly.
Developers differentiate between ‘strong AI’ and ‘weak AI’. Strong AI, sometimes called general AI, refers to a machine able to solve any problem requiring advanced cognitive abilities. It would be able to deal with new situations and solve problems it has never faced before, not confined only to chess.
That is the technical explanation. Another way of looking at it is that unlike humans, AlphaZero has no consciousness of its actions. In other words, AlphaZero is not only unaware that it is playing chess, but also unaware about anything else. It is capable only of performing pre-programmed tasks, however brilliantly.
In 2017, IEC and ISO became the first international standards development organizations (SDOs) to set up a committee to carry out standardization activities for artificial intelligence. Subcommittee (SC) 42 is part of the joint technical committee ISO/IEC JTC 1.
SC 42 is working with other JTC 1 subcommittees, such as those addressing the internet of things, IT security, and IT governance, as well as the IEC Systems Committee (SyC) for Smart Cities.
SC 42 has set up a working group on foundational standards to provide a framework and a common vocabulary. Several study groups have been set up to examine the computational approaches and characteristics of AI systems, trustworthiness, use cases and applications and big data.
In addition to the joint committee with ISO on AI, IEC is a founder member of the Open Community for Ethics in Autonomous and Intelligent Systems (OCEANIS). It brings together standardization organizations from around the world with the aim of enhancing awareness about the role of Standards in facilitating innovation and addressing issues related to ethics and values.
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