News – Blog
Meet Bob: AI job coaching tech and CareerTech Challenge winner
29 March 2021
Guest blog by Joanna Beaufoy and Tom Dixon
The winner of the CareerTech Challenge, securing £120,000 for producing their job coaching tech called Bob, was announced this week.
We spoke to Joanna Beaufoy, Product Manager from Bayes Impact and Tom Dixon, Research and Project Lead, from ACH to learn more about how Bob came to be and what they have learnt along the way during the challenge prize process.
What is Bob?
Bob is an open-source job coaching technology developed by non-profit Bayes Impact, with the idea to use open data on the labour market to empower job seekers to do something about their job search. What’s different about Bob is that it doesn’t rely on matching tech, nor finding a pre-made “solution” for anyone. Instead it empowers it’s users to understand where they are in the job market and what they could actively do in their own situation, instead of simply matching them to opportunities.
To help adapt Bob to the UK and understand the needs of local job-seekers, Bayes Impact, joined up with ACH in the UK, who deliver impactful support and integration services for refugees, BAME & migrant individuals. The UK version of Bob is already showing potential, despite it only being it’s first version.
Why is Bob so important?
Bob has been used to help maximise potential for refugees and migrants, removing unconscious bias from processes, which is important for Tom Dixon, at ACH. He says:
I have seen a lot of unconscious bias, where people meet a refugee at an appointment and there is already an assumption about the types of work that person can do – such as cleaning for women and warehouse type jobs for men. And the structurally built systems can be damaging to those people and wider UK society by not maximising the full potential of the people who live here.
Joanna Beaufoy from Bayes Impact agreed that the inequality of information for job seekers is prevalent, but this inequality is also currently widely accepted. Bob wants to change that. Joanna mentioned that it can be difficult for job-seekers to find the information they need, let alone understand how to apply it to their own circumstance. . As the wealth gap grows, the need and the potential for information sharing in tech like Bob is huge, and this is only the beginning for the project. She says:
The empowering nature of Bob is about helping people be critical about job search promises and helping them through the complexities of it. It is not just about getting your CV up on a site and waiting to see what happens.
Watch to learn more about Bob’s innovative solution
What were the pros and cons of being involved in a challenge like this?
Although the pandemic threw everyone for a loop, and created difficulties in ways of working (for instance the two teams have never met in person), the support and guidance that the challenge and Challenge Works provided for the teams was deemed as invaluable.
The range of experts the Bob team got to work with through Challenge Works, who were happy to work over Zoom, boosted morale, and were highly skilled, were available for us even on an adhoc basis has been amazing. The Data Analytics Team at Nesta has helped us feel more connected.
Winning this prize means that the Bob UK team can now put more resources and confidence into their approach, as well as support their work financially.
Winning this means we can continue our work but also help develop our tech to prevent more people from being left behind.
What advice would you give to anyone participating in a prize process?
While the team was prepared to take the risks that they did, their biggest learning was around being flexible as the pandemic hit. While external influences impacted their work they also realised along the way that being flexible in general with the “challenges of the challenge” would also serve their work well.
Joanna stated as a turning point in the competition:
Shedding the skin of your brand, organisation and team to work with others was also a learning. In the first few weeks, meeting all the various players, it was unclear how competitive it would be, and in the end we had to learn to be humble and ask when we really needed the help.
As both partners are relatively modest organisations, they learnt it was in their best interest in working towards a common goal to be open and collaborative, learning along the way.
At the end of the day, Bob aims to have a majority of their users understand the main challenges and resources to act on the barriers they face in the job market. As long as users understand what is standing in their way and what they can do to help themselves, then the Bob team knows they are making an impact. Another aim is to draw attention to gaps in the labour market, so there is more awareness around creating pathways that are accessible to job-seekers and so that others can benefit from open source tools like Bob.
Organisations with information or services they’d like recommended by Bob can contact Bob’s content team at [email protected], or read more about the technology on Bayes Impact’s website.