In the sixth episode of our “In Conversation with…” podcast series for 2023, Lucy Lewis, Partner at Lewis Silkin LLP speaks to Nimmi Patel, Head of Skills, Talent and Diversity at techUK and advisory board member of the Digital Futures at Work Research Centre.
“The impact of generative AI is expected to vary from industry to industry and people have said it can cause significant disruption. But, email caused significant disruption, the printing press caused significant disruption, and I think we can handle it as long as we focus on people first solutions.”
The launch of ChatGPT has reignited the debate about how advances in technology could reshape the world of work. In this podcast, Nimmi and Lucy explore the opportunities and challenges that automation and emerging AI technologies present and the extent to which these technologies can be leveraged to create good work and more diverse and inclusive workplaces.
Key takeaways from the conversation:
- Jobs are at risk (but jobs will also be created): more than 6,000,000 people in the UK are employed in occupations that are likely to radically change or disappear entirely by 2030 due to technological progress and changing demographics. However, the adoption and use of AI will generate opportunities for the creation of new innovative jobs.
- Humans will work alongside tech: AI will not be able to replace human judgement and it is the responsibility of humans to decide how to teach it, deploy it and acquire the skills they need to thrive in the workplace of the future.
- Risks of algorithmic bias: while the risk of biases in AI are not new, generative AI’s ready accessibility to public data may magnify the risk. Maintaining trust in AI development will be essential and regulation will play a key role.
- AI can enhance DE&I: deploying AI in recruitment can mitigate biases in traditional decision-making and increase the pool of applicants.
- The metaverse presents opportunities: building the metaverse gives us the chance to better reflect our humanity and remove societal biases.
