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Contenido proporcionado por Carnegie Mellon University Software Engineering Institute and Members of Technical Staff at the Software Engineering Institute. Todo el contenido del podcast, incluidos episodios, gráficos y descripciones de podcast, lo carga y proporciona directamente Carnegie Mellon University Software Engineering Institute and Members of Technical Staff at the Software Engineering Institute o su socio de plataforma de podcast. Si cree que alguien está utilizando su trabajo protegido por derechos de autor sin su permiso, puede seguir el proceso descrito aquí https://es.player.fm/legal.
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Measuring the Trustworthiness of AI Systems

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Contenido proporcionado por Carnegie Mellon University Software Engineering Institute and Members of Technical Staff at the Software Engineering Institute. Todo el contenido del podcast, incluidos episodios, gráficos y descripciones de podcast, lo carga y proporciona directamente Carnegie Mellon University Software Engineering Institute and Members of Technical Staff at the Software Engineering Institute o su socio de plataforma de podcast. Si cree que alguien está utilizando su trabajo protegido por derechos de autor sin su permiso, puede seguir el proceso descrito aquí https://es.player.fm/legal.

The ability of artificial intelligence (AI) to partner with the software engineer, doctor, or warfighter depends on whether these end users trust the AI system to partner effectively with them and deliver the outcome promised. To build appropriate levels of trust, expectations must be managed for what AI can realistically deliver. In this podcast from the SEI’s AI Division, Carol Smith, a senior research scientist specializing in human-machine interaction, joins design researchers Katherine-Marie Robinson and Alex Steiner, to discuss how to measure the trustworthiness of an AI system as well as questions that organizations should ask before determining if it wants to employ a new AI technology.

  continue reading

430 episodios

Artwork
iconCompartir
 
Manage episode 379613335 series 2487640
Contenido proporcionado por Carnegie Mellon University Software Engineering Institute and Members of Technical Staff at the Software Engineering Institute. Todo el contenido del podcast, incluidos episodios, gráficos y descripciones de podcast, lo carga y proporciona directamente Carnegie Mellon University Software Engineering Institute and Members of Technical Staff at the Software Engineering Institute o su socio de plataforma de podcast. Si cree que alguien está utilizando su trabajo protegido por derechos de autor sin su permiso, puede seguir el proceso descrito aquí https://es.player.fm/legal.

The ability of artificial intelligence (AI) to partner with the software engineer, doctor, or warfighter depends on whether these end users trust the AI system to partner effectively with them and deliver the outcome promised. To build appropriate levels of trust, expectations must be managed for what AI can realistically deliver. In this podcast from the SEI’s AI Division, Carol Smith, a senior research scientist specializing in human-machine interaction, joins design researchers Katherine-Marie Robinson and Alex Steiner, to discuss how to measure the trustworthiness of an AI system as well as questions that organizations should ask before determining if it wants to employ a new AI technology.

  continue reading

430 episodios

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