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Toward a Bias-Aware Future for Mixed-Initiative Visual Analytics
arXiv - CS - Human-Computer Interaction Pub Date : 2020-11-19 , DOI: arxiv-2011.09988
Adam Coscia (1), Duen Horng Chau (1), Alex Endert (1) ((1) Georgia Tech)

Mixed-initiative visual analytics systems incorporate well-established design principles that improve users' abilities to solve problems. As these systems consider whether to take initiative towards achieving user goals, many current systems address the potential for cognitive bias in human initiatives statically, relying on fixed initiatives they can take instead of identifying, communicating and addressing the bias as it occurs. We argue that mixed-initiative design principles can and should incorporate cognitive bias mitigation strategies directly through development of mitigation techniques embedded in the system to address cognitive biases in situ. We identify domain experts in machine learning adopting visual analytics techniques and systems that incorporate existing mixed-initiative principles and examine their potential to support bias mitigation strategies. This examination considers the unique perspective these experts bring to visual analytics and is situated in existing user-centered systems that make exemplary use of design principles informed by cognitive theory. We then suggest informed opportunities for domain experts to take initiative toward addressing cognitive biases in light of their existing contributions to the field. Finally, we contribute open questions and research directions for designers seeking to adopt visual analytics techniques that incorporate bias-aware initiatives in future systems.

中文翻译:

迈向混合主动视觉分析的偏见感知未来

混合主动式可视化分析系统结合了完善的设计原则,可以提高用户解决问题的能力。当这些系统考虑是否主动实现用户目标时,许多当前的系统静态地解决人类主动性中潜在的认知偏差,依赖于他们可以采取的固定主动性,而不是在偏差发生时识别、交流和解决偏差。我们认为,混合主动设计原则可以而且应该通过开发嵌入在系统中的缓解技术直接纳入认知偏差缓解策略,以解决原位认知偏差。我们确定机器学习领域的专家采用可视化分析技术和系统,这些技术和系统结合了现有的混合倡议原则,并检查他们支持偏见缓解策略的潜力。该检查考虑了这些专家为视觉分析带来的独特视角,并位于现有的以用户为中心的系统中,这些系统示范性地使用了由认知理论提供的设计原则。然后,我们建议领域专家根据他们对该领域的现有贡献采取主动解决认知偏见的知情机会。最后,我们为寻求采用可视化分析技术的设计师提供开放性问题和研究方向,这些技术在未来的系统中结合了偏见感知计划。该检查考虑了这些专家为视觉分析带来的独特视角,并位于现有的以用户为中心的系统中,这些系统以认知理论为依据的设计原则进行了示范。然后,我们建议领域专家根据他们对该领域的现有贡献采取主动解决认知偏见的知情机会。最后,我们为寻求采用可视化分析技术的设计师提供开放性问题和研究方向,这些技术在未来的系统中结合了偏见感知计划。该检查考虑了这些专家为视觉分析带来的独特视角,并位于现有的以用户为中心的系统中,这些系统示范性地使用了由认知理论提供的设计原则。然后,我们建议领域专家根据他们对该领域的现有贡献采取主动解决认知偏见的知情机会。最后,我们为寻求采用可视化分析技术的设计师提供开放性问题和研究方向,这些技术在未来的系统中结合了偏见感知计划。然后,我们建议领域专家根据他们对该领域的现有贡献采取主动解决认知偏见的知情机会。最后,我们为寻求采用可视化分析技术的设计师提供开放性问题和研究方向,这些技术在未来的系统中结合了偏见感知计划。然后,我们建议领域专家根据他们对该领域的现有贡献采取主动解决认知偏见的知情机会。最后,我们为寻求采用可视化分析技术的设计师提供开放性问题和研究方向,这些技术在未来的系统中结合了偏见感知计划。
更新日期:2020-11-20
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