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EveryBOTy Counts: Examining Human-Machine Teams in Open Source Software Development.

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Summary
This summary is machine-generated.

Adding bots to software teams boosts productivity and communication, but may increase workload. This study explores human-machine teaming in the future of work.

Keywords:
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Area of Science:

  • Computer Science
  • Human-Computer Interaction
  • Organizational Behavior

Background:

  • Machine agents, particularly bots, are increasingly integrated into sociotechnical systems.
  • These agents play a more active role in collaborative work, necessitating research into their impact.
  • Understanding human-machine teaming is crucial for the future of work.

Purpose of the Study:

  • To compare productivity between human-only and human-machine teams.
  • To characterize similarities and differences in coordination within these team structures.
  • To investigate the role of bots in collaborative work environments.

Main Methods:

  • Analysis of hundreds of open-source software project teams.
  • Examining the association between the presence of bots and productivity outcomes.
  • Quantifying communication patterns and work centralization in teams.

Main Results:

  • Teams with bots exhibited higher productivity.
  • The presence of bots was linked to increased work centralization and communication.
  • Potential tradeoffs include increased productivity alongside a higher workload.

Conclusions:

  • Bots can enhance productivity and communication in software development teams.
  • The integration of bots presents a complex dynamic with potential benefits and drawbacks.
  • Findings inform the advancement of human-machine teaming research and practice.