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Fostering human–machine collaboration

collaboration

Companies that blend machine and human collaboration will have the most effective teams, according to a McKinsey report.

Organisations that adopt the twin goals of creating an intellectual division of labour that distributes processing power can build a culture that incorporates collaborative and trustworthy hybrid intelligence, according to a McKinsey report by Stefan Moritz and Kate Smaje.

Modern machine superpowers, fast and accurate computation and the ability to ingest terabytes of data, seem to be almost the opposite of some of today’s most sought-after human qualities such as creativity, empathy, critical thinking, and emotional intelligence.

When considering the intersection of machines and humans and how to establish a supportive environment, leaders should seek a deeper understanding of the team’s needs and goals as well as a more holistic view of the opportunities available through interaction. A focus on five actions can help:

Redesign work environments for teams inhabited by people, machines, and data.

Rethink the work rituals and norms we live by in our roles to foster inclusivity and trust among machines and people.

Help machines interpret human movement, mood, and thought and respond with appropriate information or feedback.

Provide training and encourage experimentation for leaders and teams to learn, demystify, and create shared experiences to build trust.

Identify new opportunities for human–machine interaction and orchestrate pilots or lighthouses in a setting where solutions can be improved iteratively and then scaled.

Machines could also be programmed to do their share. Machines could be programmed to surpass humans at recognising emotions and empathy, but granting machines the ability to act on information in ways that connect with humans will likely prove more difficult.

. If companies could build team-mate algorithms that cause machines to behave in more inclusive and collaborative ways, machines could make humans far more enthusiastic about their jobs. This task is not easy, and the aim is not to make machines human. They are limited by what we enable them to do but we haven’t explored the hybrid intelligence well enough yet.

By extending the emphasis on collaboration and inclusion to machines, organisations may spark new thinking and debate about these issues and how to make them influence positive outcomes.

Communication is going to be a barrier for human–machine teams. But, as with all relationships, organisations must first put in the time to become comfortable with viewing machine intelligence as a peer rather than as merely a tool, and then determine the contours of that relationship.

The biggest opportunity for human–machine collaborations might be the potential of outlearning competitors. The human–machine debate is challenging what we know about technology and interactions: what a successful team might look like, how people and technology can interact for success, and what it means to be social.

If an organisation were to shift its approach to machines from ‘them versus us’ to ‘we’, it could facilitate the continued integration of machines into the workforce and yield tremendous collaboration effectiveness and increased well-being.

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