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Post by Niamh Walsh, Learnovate
Humans are complicated. It starts from childbirth. Evolution requires us to twist and turn on our way out into the world in a process far more complex, and risky, than any other mammal. The reason for this difficult and arduous process is the size of our brains. The human body pushes itself to the limit to accommodate the size of the human brain.
Advances in artificial intelligence (AI) and machine learning (ML) mean that we can increase our capacity and capability by amplifying our human brainpower with artificial mental power. Can intelligent systems relieve this pressure on human evolution to accommodate ever more powerful brains?
Learnovate attended the Learning Technologies 2019 conference on organisational learning and the technology that supports learning at work on Wednesday, 13 and Thursday, 14 February in London’s Docklands. With published reports on the impact of AI and ML on corporate learning and using ML to tag learning content, we were curious to hear the latest thinking from the Learning Technologies keynotes on this subject.
Daniel Susskind – Fellow in Economics at Balliol College, Oxford University – was Learning Technologies’ keynote speaker exploring ‘The future of work: technology, myths and the importance of learning’. He enticed us with a vision of a future of work where increasingly capable systems enhance the capacity and capability of human managers.
Technology is increasingly capable, increasingly pervasive, and increasingly connected through the Internet of Things (IoT). The exponential growth in the power and capability of technology is matched by the precipitous fall in its cost year on year. Susskind projects that by 2050 computers will exist that surpass the processing power of humankind.
Susskind does not become mired in philosophical angst about robots v humans. The question ‘Can machines think?’ is irrelevant says Susskind. He quotes MIT’s revered Professor of AI Patrick Winston: “There are lots of ways of being smart that aren’t smart like us”. Computers are increasingly capable, non-thinking machines that can solve our problems in an unhuman way. Technology doesn’t need to be ‘smart like us’ to solve our problems. Not being ‘smart like us’ means that computers are much better than humans at dealing with uncertainty.
Susskind debunks the dystopian vision of machines precipitating a bleak future of mass unemployment. He believes the question ‘Will robots take my job?’ is the wrong question. Robots are not coming for our jobs – they are coming to take over our tasks. Susskind argues that technological change will not make entire roles redundant across the economy.
Instead, certain tasks and activities within a role will be mediated by systems. He reports that for 60 per cent of jobs, automation may replace 30 per cent of tasks. While many people accept that blue-collar jobs will be impacted, Susskind highlights people’s stronger resistance to a future impact on white-collar jobs. With technology now composing music, creating art and reading human facial expressions, white-collar roles will be impacted.
The other keynote speaker at Learning Technologies 2019 was Marcie Conner, CEO of US company Impact Ingenuity, with her opening address: ‘Can we be candid? Learning at the intersection of risk, change, machine and meaning.’ Conner argued the importance of experts is waning as knowledge becomes more freely accessible to all. In the past, organisations valued employees who had knowledge. Now companies want employees who can act on data presented to them. According to Conner, what we decide to do with data generated and retrieved by intelligent systems is now more important than accessing the limited knowledge we can store in our own individual human brains.
There is little doubt that technology will transform the work of human experts. Both Conner and Susskind predict the demise of human experts as intelligent systems provide access to specialist knowledge once held by the few. Just as Nietzsche proclaimed the death of God when people no longer relied on monarchs and priests for authority in the age of enlightenment, humans will no longer rely on the authority of experts because machines will store far more data and cases for comparison than any human ever could.
This ‘death of experts’ will be incremental but transformative, says Susskind, and will affect traditional professionals such as doctors, lawyers, teachers, accountants, tax advisers, management, consultants, architects and journalists. Their expertise will be liberated from human brains – transforming the way we produce and distribute expertise in society. Non-experts will be supported to achieve their objectives by accessing knowledge provided by technology instead of accessing knowledge once held in the heads of experts.
These changes in the way expertise is made available will be fundamental and irreversible. Conner argues that, more than ever, workers must be smart, curious and agile. This is the workforce that employers need, but these are also the individuals needed by our communities and by society. People working in education and learning have an essential role in capturing, cultivating, and curating this knowledge. As individuals, we are each responsible for our part in forming the collective knowledge and power of the human race.