Collective [Human & Machine] Intelligence

What’s more intelligent, people or machines?

What if … we wouldn’t have to choose?

Collective Intelligence Playbook, NESTA
  • Understand Problems Generate contextualised insights, facts and information on the dynamics of a situation.
  • Seek SolutionsFind novel approaches or tested solutions from elsewhere. Or incentivise innovators to create new ways of tackling the problem.
  • Decide and ActMake decisions with, or informed by, collaborative input from a wide range of people and/or relevant experts.
  • Learn and AdaptMonitor the implementation of initiatives by involving citizens in generating data, and share knowledge to improve the ability of others.

Collective Crowdsourcing

Illustration, Breadline
Illustratio nOSR4Rights, Source: nesta.org.uk
“Is there a perfect mum?”, source: HappyFinish

What’s in for us?

Getting Started …

  • What are all factors that contribute to a system’s intelligence?
  • Which (machine) team (algorithm working with data experience) are we putting on which tasks?
  • What data set, aka experience, are we hiring?
  • What are biases within that experience?
  • Which tools and algorithms are we hiring?
  • Which (human) team are we putting on which tasks?
  • Who contributes content?
  • Who contributes evaluation/rating/training?
  • Who reacts to other actors output?

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UX Research & Design at #trlabs London, w/ brilliant data science & vis team. curious about UX, IA & design thinking. Posts solely reflect my personal opinion.

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Johannes Schleith

Johannes Schleith

UX Research & Design at #trlabs London, w/ brilliant data science & vis team. curious about UX, IA & design thinking. Posts solely reflect my personal opinion.

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