************Apologies for multiple posting *************
Please distribute this call to interested parties
Workshop on “Teaching HCI for AI: Co-design of a Syllabus”
An event of SIGCHItaly (ACM SIGCHI Italian Chapter)
in collaboration with
CINI AIIS Lab (Artificial Intelligence and Intelligent Systems Lab)
Rome, July 7th, 2020
Dip. Ingegneria Informatica Automatica e Gestionale "Antonio Ruberti"
Sapienza Università di Roma, Via Ariosto, Roma
/// Submission deadline: June 15th, 2020 ///
The safety and well-being of prospective participants is our priority.
We are therefore ready to hold the workshop online if restrictions due to COVID-19 will not allow us to conduct it physically in Rome.
Compared with traditional technologies, AI-based technologies hold different expectations from a user’s perspective. Besides the established principles of user-centered design, there are further important aspects that are peculiar to this type of system and that need to be considered during design.
Intelligent system components usually have probabilistic behaviors, based on nuances of tasks and settings, which can confuse users, erode their confidence, and lead to the abandonment of AI technology. AI designs show high variability: they vary in capabilities and interaction styles, impacting user engagement and usability.
High-profile reports of failures, ranging from humorous and embarrassing (e.g., autocompletion errors) to more serious situations in which users cannot effectively understand or control an AI system (e.g., collaboration with semi-autonomous cars), might harm users. These factors, among others, show that designers and developers need proper knowledge as well as proper methodologies and techniques to create effective intelligent systems that may better satisfy the users. It also highlights the need for the end users to have control over the system:
this can be achieved on one side by granting transparency of the system behaviour, and on the other side by empowering the end users to configure the system behaviour.
Given this scenario, it is important that future AI specialists become aware of the potential ethical and practical issues of this type of system, as well as acquire theoretical competences and methodological skills to properly design them. This requires adopting a perspective that considers the users and their needs to let them understand and control AI-based technologies.
There is already some discussion on the need for guidelines for designers (for example, Google People+AI, Microsoft Guidelines for Human-AI Interaction and IBM research on the intersection of HCI and AI as well as some interesting research venues (explicability, algorithm aversions/appreciation, uncanny valley, etc.). Yet, we still miss a rationalized syllabus explicitly prepared for AI technical courses that might guide the teaching of HCI concepts for AI technical students. The emphasis should not only be on specific interaction techniques (such as gestures or voice), rather on understanding how HCI methods and principles can help design “human-in-the-loop” AI systems, which implies considering who AI systems are built for and evaluating how well those systems are working.
The workshop aims to bootstrap a working group to prepare a syllabus for a course for teaching HCI skills to designers of AI interactive systems. Therefore, target participants are both AI researchers with an interest in interaction aspects and HCI researchers with interests in aspects related to interaction with AI systems
During the workshop, a short brainstorming activity will elicit important topics that need to be covered by the syllabus. Then, parallel group sessions working on a first draft will follow. The syllabus should mandate a set of core topics, i.e., valid across different study programs, and suggest additional material to accommodate the specificity of the different programs where the course could be offered. The draft of the syllabus will be finalized in a few working sessions after the workshop, with the goal of publishing it (for example as a paper in the Interaction magazine, or in a major HCI or AI conference) for wider feedback.
Participants are solicited to submit a visionary statement (two pages of max 1000 words, references included) on the aspects that are deemed important for the syllabus the Workshop focuses on. The accepted statements will be published online on the Workshop Web site and will stimulate the discussion during the workshop. With the goal of proposing proper items for the syllabus, the submitted statements should discuss the following questions:
- What are examples of AI systems that pose problems to the users, such as ambiguities that confuse users, lack of control, lack of trust, …
- What are examples of failures of AI systems possibly due to misapplications of HCI theories, principles and methodologies?
- What are the interaction paradigms/modalities/metaphors for AI systems that best support the interaction with users?
- What are design, development and user testing methods and practices currently adopted in AI?
- What are design, development and user testing methods and practices available in HCI that could be adopted in AI?
- What theories and design methodologies should be used for creating AI systems that best empower people?
Contributions should be submitted through Easychair, at the address:
***Deadline for submitting the vision statement: June 15th, 2020***
***Notification to authors: June 22nd, 2020***
M. Francesca Costabile, Università di Bari ALDO MORO
Cristina Gena, Università di Torino
Maristella Matera, Politecnico di Milano (SIGCHI Italy Chair)
Fabio Paternò, ISTI-CNR, Pisa
Genny Tortora, Università di Salerno
Massimo Zancanaro, Università di Trento and FBK (SIGCHI Italy Vice-Chair)
Tiziana Catarci, Sapienza Università di Roma
Luca Console, Università di Torino
Fulvio Corno, Politecnico di Torino
Giuseppe De Giacomo, Sapienza Università di Roma
Alberto Del Bimbo, Università di Firenze
Rino Falcone, CNR-Roma
Salvatore Gaglio, Università di Palermo
Luciano Gamberini, Università di Padova
Antonio Krüeger, German Research Center for AI (DFKI), Germany
Patrizia Marti, Università di Siena
Roberto Navigli, Sapienza Università di Roma
Daniele Nardi, Sapienza Università di Roma
Sharon Oviatt, Monash University, Australia
Francesco Ricci, Libera Università di Bolzano-Bozen
Ben Shneiderman, University of Maryland, USA
Albrecht Schmidt, Ludwig-Maximilians University of Munich, Germany
Oliviero Stock, FBK
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