Future efforts to tackle social issues by combining machine and human intelligence require an integration of tools into established workflows and co-operative human-machine systems, according to a new report.
Innovation charity Nesta has published the document on the second round of the Collective Intelligence Grants programme, which involved £500,000 of funding for 15 experiences beginning in the autumn of 2020
It has led the organisation to outline six priorities for future research and innovation, one of which is a need to understand how best to integrate collective intelligence tools into established workflows.
This results from a number of the experiments highlighting that the integration can be disruptive, rendering it less helpful than anticipated, and that there is a need for user research and training to make it more effective.
Secondly, while some studies have pointed to AI-only teams outperforming human-AI teams, there are also risks around a dependence on AI that leads to the need for co-operative systems, which will require innovation with a focus on group problem solving.
The other priorities are:
- establishing the right partnerships to do collective intelligence well;
- researching how to effectively recruit participants and sustain engagement;
- funding innovation in tools for collective decision making;
- and designing and testing systems that enable positive collective behaviours.
Collective intelligence is the enhanced capacity that is created when people work together, often with the help of technology, to mobilise a wider range of information, ideas and insights.
The experiments fell under one of four themes – exploring AI-crowd interaction; making better collective decisions; understanding the dynamics of collective behaviour; and gathering better data – and the report highlights case studies from the programme.
Involving different groups
Kathy Peach, co-director at the Centre for Collective Intelligence Design, said: “We shouldn’t pit humans against machines, but rather design AI that improves our ability to co-operate with technology and each other, extending human intelligence rather than attempting to replicate it. It also highlights how we can involve diverse groups of people to help create more representative AI, as well as leveraging AI to overcome human biases.
“The Collective Intelligence Grant Programme report is a vital example of the research we need to undertake in order to better understand how best to combine these forms of intelligence and we need to ensure that investment is targeted at the right places to continue innovation in this field.”
Image from iStock, Andrey Popov