Meeting of the Parliament 13 November 2019
Thank you for making that invitation, Presiding Officer.
I welcome these debates for no less a reason than the one that Emma Harper just demonstrated: they provide us with an excuse to cite “Star Trek” without embarrassment. Patrick Harvie is laughing; however, I know that when he was describing his iPhone, he had in his mind a “Star Trek” data PADD.
Some of the dilemmas that are faced in science fiction are the very debates and dilemmas that we are considering today. However, they are also age-old dilemmas, because we have been facing the consequences of technology since we came into being. That can be seen from the invention of the wheel—a bit of technology that meant that we no longer had to rely on what we could lift on our back to carry items around with us—to the printing press, where a machine enabled us to print, almost instantaneously, a page that it would have taken a scribe an hour or so to produce. Then there is the computer, which used to be a person rather than a machine.
We have always had to deal with the consequences of technology change, and that technology change has invariably taken labour away from people and given it to machines. However, there is a difference now, and we need to be careful. Some people out there say that we have always had to deal with such change and that there is nothing new about it, but the pace and scope of the change are new. We have never before faced technologies that replace almost the entire supply chain or the complete scope of a human activity. That is the prospect that we are looking at with AI. We are looking at technology that has moved from robots that simply make widgets to algorithms that can analyse and plan, and we see jobs in accountancy and law, for example, being taken over by machines.
As well as looking at the what, we need to look at how the technology is replacing activities. Many members have talked about AI and automation, but nobody has really talked about machine learning. There are real challenges with machine learning. Artificial intelligence can learn to do things and carry out tasks very efficiently, but it cannot necessarily describe its own rules and algorithms, which it uses to do them. That is one of the defining aspects of machine learning. Previously, we were able to have accountability and to explain how things were done, but one of the key challenges with AI is that we might not be able to do that.
As many members have articulated, we need to ensure that we maximise opportunities. We need to minimise the impacts, but we also need to look at the new elements and issues that AI and machine learning throw up. Above all else, we need to ensure that we facilitate the transition. I will speak briefly about the three key elements that we need to focus on in relation to the transition.
My colleague Rhoda Grant outlined the vital importance of having a robust industrial strategy with AI at its core and serious investment at its heart. We should consider the industrial change that we have experienced in the recent past. We have got things wrong in failing to invest in new technologies. We lost heavy industries in Scotland because this country failed to invest in new technologies as they came in. That is why people lost their jobs.
Investments in much technology change, from GPS and satellites to the algorithms that allow phones to recognise people’s speech, were backed by state investment. We will be able to embrace the technology only by having a serious industrial strategy that is backed by state investment that can absorb the risks that individual companies cannot absorb.
Likewise, we must ensure that our people have skills. A number of members have talked about the skills that are imparted in school, for example. It is not just a matter of what skills our people have; it is also a matter of their ability to reskill time and again. It is critical that we stop viewing education as a linear pathway through life—a number of members have alluded to that. The reality is that, with the pace and nature of change, people will have to skill and reskill multiple times through their working lives. There cannot be apprenticeships that people can take only once in their career or undergraduate degrees that will be paid for only once. We need to look fundamentally at our education system to ensure that people can skill and reskill.
We also need to look at the impact on the state.