Girls and people from disadvantaged backgrounds are currently less likely to choose subjects that develop the skills needed for digital and data science careers.
If our world is going to be driven by artificial intelligence algorithms, yet huge sections of society are underrepresented when deciding how these are programmed, then we have a problem.
This has to change. Our education system must be multi-disciplinary and based on real-life problem-solving. Students need technical and creative skills. Colleges need better links with industry to give their students the academic and vocational skills needed for the jobs of the future.
Gone are the days when you could study until the age of 18, then work in one job forever. Kids today are going have 11 different jobs, if not more. We need to instil the resilience to adapt to change, the ability to learn and evolve, and a lifelong learning attitude.
We must also make sure that teachers, learners and the education system use technology, such as artificial intelligence and big data, to make better decisions. Education must be accessible, personalised and engaging.
We also need more opportunities in vocational education for work experience and placements, because so many students graduate without any exposure to the world of work. We need to build that in, so that every student has an opportunity to develop their skills and gain valuable access to employers.
There are issues around equity here. Social capital matters and a lot of people get their jobs through connections. For those who don’t have those connections, work experience and use of technology to connect with people are crucial. Technology can be a great force for good in addressing this equity challenge.
People say that the lack of role models deter women from studying and working in technology - but, while role models are powerful, I think it's more than that. We need to build women’s technical skills, creative skills, social and emotional skills to enable them to really thrive in the workplace. It’s also about confidence. A lot of girls, even though they outperform boys in school, don't go on to study or work in technical fields, because they are not confident. We have to bridge that gap.
Another important area is around opportunity; how can we change hiring practices so that employers are aware of their unconscious bias, and are recruiting people not based on their name or gender or ethnic or racial background but based on their skills and capabilities? For that, Nesta has invested in a company called Be Applied. It doesn't show the CV or name of the person, it just shows answers to certain questions. Based on that, employers decide whether to interview them. The more we can use technology to overcome biases and unfair practices, the better the outcome is going to be.
The future of AI in education is uncertain. To a large extent, it depends on decisions we make now – from investment in R&D to training of teachers, governance of data, and managing the ethical implications of AI tools. If we don't make changes to prepare young people for the future, we are not helping learners realise their true potential.
Rather than focusing on the skills that make us truly human – creativity, empathy, problem-solving and social skills - we are preparing students for rote-learning. This has huge consequences for the economy, productivity levels, and our wellbeing.
This blog is based on an interview from the Digifest magazine 2019. Delegates can hear Joysy's keynote presentation, ‘how to create a broader, fairer and smarter education system’, at 09:30 on day two of Digifest, Wednesday 13 March, in Hall 1.