Human-AI collaboration requires refined group-awareness concepts for asymmetrical relationships between users and AI partners¶

Claim · All claims
Evidence · 1 study · theoretical r2 · q1
Currency · newest study 2023 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q1 i? In human-AI interactions, the concept of group awareness needs to be refined to allow for more asymmetrical relationships, since humans may know about the AI's competencies and shortcomings while the reverse is uncertain. → Ulrike Cress · Joachim Kimmerle 2023

Evidence¶

Ulrike Cress · Joachim Kimmerle 2023¶

Ulrike Cress · Joachim Kimmerle. (2023). Co-constructing knowledge with generative AI tools: Reflections from a CSCL perspective. Intern. J. Comput.-Support. Collab. Learn. https://doi.org/10.1007/s11412-023-09409-w

q1 · i? · theoretical · r2

Theoretical argument extending group awareness research to human-AI collaboration. The authors note awareness requires users to know the training basis and output generation of the tool, and it remains open whether the AI partner can create awareness of its partner.

"Research has described the relevance of group awareness (the perception of certain characteristics of a group and its members) for interaction among humans (e.g., Engelmann et al., 2009). In this new format of human-AI interactions, the awareness concept needs to be refined to allow for more asymmetrical relationships."

Discussion¶

Related Claims¶

• In interviews with 25 engineering students at one Swedish university, students described GenAI as acceptable when it stimulates reflection and directly copying its outputs as cheating, and one used its fallibility as a prompt to double-check — related
• Students' main AI challenges are content reliability and depth, and most expect AI to serve as tutor, creative partner, and critical thinking partner rather than mere content generator — related
• Role metaphors positioned GenAI as helper, learning partner, and friend/foe, with a high proportion combining friend and foe — related
• Working with imperfect AI outputs under mentor supervision was followed by students developing skepticism and independent debugging skills — related
• AI-assisted ideation was conditionally acceptable when researchers retained decision-making authority, but problematic when it displaced conceptual labour — related
• AI systems are non-neutral socio-technical artifacts embedding cultural assumptions and power relations — a broader claim this one bears on
• AI connectedness is psychologically real but ethically asymmetric, carrying conditional rather than inherent risks — related
• Using generative AI as a dialogic partner for brainstorming, feedback, and co-construction can support constructive and interactive learning — related
• Evidence exists for AI agents as collaborative partners, but more work is needed on how computing agents can best support learning of AI itself — related
• Argumentative dialogs between humans and generative AI can support knowledge transformation when prompted appropriately — related
• Awareness prompts stimulated discourse about more concepts but did not improve shared drawing quality in elementary dyads — related