AI is advancing fast, but the human element is still, and always will be, required in many business roles.

That was the theme of our recent Illuminate dinner with guest speaker Oliver Williams, head of financial markets at Alpha Development. Oliver oversees all technical content and related programs, with a focus on integrating data science and technology into the financial curriculum.

At the event, Oliver spoke about the shift in labour and employment trends, from the dominance of farming and manual labour in the 1870s through to manufacturing in the 1980s to retail; which he believes to be the largest sector today. Nowadays data science is a huge trend, as we work towards a future driven by data and machine learning. In fact, data scientist was described as the ‘sexiest job of the 21st century’ in a 2012 Harvard Business Review article by Thomas H. Davenport and D.J. Patil.

But when we consider which roles will be ‘replaced by robots’ we must consider the human element. HR and L&D professionals are less likely to be replaced completely because human interaction is so important for these roles. Recent attempts to use machine learning for recruitment, for instance, show that a machine is only as unbiased as the people who’ve built and programmed it. It’s very hard – perhaps not possible – to teach a machine context or empathy.

The key to making our work lives easier using tech is to find the complementary tasks which can be achieved by a machine.
Oliver also talked about the need for strong design in technology. User-centred design is vital – products and systems must be made to work around the needs and emotions of humans and how they react to situations. Design-thinking itself requires skills of empathy, reasoning and understanding.

Long-term labour trends mean we move away from a prevalence of physical strength roles to intellectual ability roles, emotional intelligence is required too. And this is a key consideration when training and developing for technical roles. According to our recent research, students and graduates are keen to develop both technical ability and soft skills as they enter the workforce – coding was listed alongside management and networking skills as a priority.

When considering ways to integrate data science and design into the business, a traditional classroom-based style of learning isn’t going to be enough. Nor is online learning alone. Oliver suggests a combined L&D programme ‘with features like high-touch coaching, hackathons and learning conferences’. Reverse mentoring is also a strong way to develop early talent by using their digital skills and knowledge to support senior colleagues.