Experiential AI

Hemment, Drew; Aylett, Ruth; Belle, Vaishak; Murray-Rust, Dave; Luger, Ewa; Hillston, Jane; Rovatsos, Michael; Broz, Frank

doi:10.1145/3320254.3320264

Cited by 11 publications

(7 citation statements)

References 15 publications

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“…However, it is unclear how ML uncertainty can be framed specifically for design research. For example, Hemmentt et al call for artistic, designerly practices of revealing the "distortions in the ways in which algorithms make sense of the world" [29]; yet do not outline how this may relate to existing design research methodologies as well as actual ML technologies. In the following, we discuss how the philosophical framework of postphenomenology offers a starting point to expand on this gap.…”

Section: Design Research In ML and Emerging Technologiesmentioning

confidence: 99%

Machine Learning Uncertainty as a Design Material: A Post-Phenomenological Inquiry

Benjamin

Berger

Merrill

et al. 2021

Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems

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Design research is important for understanding and interrogating how emerging technologies shape human experience. However, design research with Machine Learning (ML) is relatively underdeveloped. Crucially, designers have not found a grasp on ML uncertainty as a design opportunity rather than an obstacle. The technical literature points to data and model uncertainties as two main properties of ML. Through post-phenomenology, we position uncertainty as one defining material attribute of ML processes which mediate human experience. To understand ML uncertainty as a design material, we investigate four design research case studies involving ML. We derive three provocative concepts: thingly uncertainty: ML-driven artefacts have uncertain, variable relations to their environments; pattern leakage: ML uncertainty can lead to patterns shaping the world they are meant to represent; and futures creep: ML technologies texture human relations to time with uncertainty. Finally, we outline design research trajectories and sketch a post-phenomenological approach to human-ML relations. CCS CONCEPTS• Human-centered computing → HCI theory, concepts and models.

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Section: Design Research In ML and Emerging Technologiesmentioning

confidence: 99%

Machine Learning Uncertainty as a Design Material: A Post-Phenomenological Inquiry

Benjamin

Berger

Merrill

et al. 2021

Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems

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“…If NOVO Cinemas provides a high-quality experience, customers are more likely to come back and recommend the theater to their friends and family. Overall, considering these factors will help NOVO Cinemas to create a successful business recovery strategy and keep their customers happy (Hemment et al, 2023). Outsource associates play a crucial role in the successful business recovery strategy at NOVO Cinemas, especially when it comes to technology availability, user attitude, customer expectations, and competition deliverance.…”

Section: Literature Reviewmentioning

confidence: 99%

Strategy for Business Recovery in NOVO Cinemas

Subramanian Iyer,

Malhotra,

Eraña Reyes Jr

et al. 2024

Kuey

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The COVID-19 pandemic has caused significant disruptions to the global economy, including the entertainment industry. NOVO Cinemas, a leading cinema chain in the Middle East, has been severely impacted by the pandemic, resulting in a significant decline in revenue and footfall. The purpose of this research is to develop a strategy for business recovery in NOVO Cinemas. Amidst the backdrop of the COVID-19 pandemic's profound impact on the global economy and the entertainment sector, NOVO Cinemas, a prominent cinema chain in the Middle East, finds itself grappling with substantial declines in revenue and attendance. Recognizing the urgent need for a path to recovery, this research endeavors to develop a comprehensive strategy tailored specifically for NOVO Cinemas. Motivated by the imperative to navigate the unprecedented challenges posed by the pandemic, the study seeks to analyze the current market dynamics and the unique ramifications experienced by the cinema industry. It aims to uncover the underlying factors contributing to NOVO Cinemas' vulnerabilities while also identifying potential avenues for revitalization and growth. Hypothesizing that a multifaceted approach encompassing technological integration, revenue diversification, and a customer-centric ethos can pave the way for NOVO Cinemas' resurgence, the research adopts a rigorous methodology. It employs a combination of qualitative and quantitative analyses, including market surveys, financial assessments, and consumer behavior studies, to glean actionable insights. The results of the study reveal nuanced insights into NOVO Cinemas' strengths, weaknesses, and untapped opportunities. It underscores the significance of embracing innovative technologies, exploring new revenue streams, and prioritizing customer satisfaction as pivotal elements of the recovery strategy. In conclusion, the research underscores the critical importance of proactive adaptation and strategic foresight in overcoming the challenges wrought by the pandemic. By offering pragmatic recommendations tailored to NOVO Cinemas' unique circumstances, this study not only provides a roadmap for its recovery but also contributes novel insights that can inform the broader strategies of cinema chains in the region.

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“…Researchers have also looked at strategies of AI artists to address complex and multi-dimensional issues alongside aesthetic and technical themes when working with creative applications of AI [30]. We identify a field of critical practice -critical AI arts -in which artists work with AI technologies and data both as medium and as theme, both as tool and as topic.…”

Section: Ai + Artmentioning

confidence: 99%

AI in the Public Eye: Investigating Public AI Literacy Through AI Art

Hemment,

Currie,

Bennett

et al. 2023

2023 ACM Conference on Fairness, Accountability, and Transparency

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Recent advances in diffusion models and large language models have underpinned a new generation of powerful and accessible tools, and some of the most publicly visible applications are for artistic endeavour. Such tools, however, provide little scope for deeper understanding of AI systems, while the growing public interest in them can eclipse notice of the vibrant community of artists who have long worked with other forms of AI. We explore the potential for AI Art -particularly work in which AI is both tool and topic -to facilitate public AI literacies and consider how tactics developed before the current generative AI boom have continued relevance today. We look at the strategies of critical AI artists to scaffold public understanding of AI and enhance legibility for non-experts. This paper also investigates how collaborations between artists and AI researchers and designers can illuminate key technical and social issues relevant to the development of AI. The study entailed workshops between three professional artists who work with AI and a cross-disciplinary set of academic participants. This paper reports on these workshops and presents the intentions and strategies expressed by the artists, as well as insights of relevance to the research community on public AI literacies. We find that critical AI art can link underlying technical systems to structural issues of power and facilitate experiential learning that is situated and embodied, valuing interpretation over explanation. The findings also demonstrate the importance of transdisciplinary conversations around art, ethics and the political economy of AI technologies and how these dialogues may feed into AI design processes.CCS Concepts: • Applied computing → Media arts; • Computing methodologies → Artificial intelligence.

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Experiential AI

Cited by 11 publications

References 15 publications

Machine Learning Uncertainty as a Design Material: A Post-Phenomenological Inquiry

Machine Learning Uncertainty as a Design Material: A Post-Phenomenological Inquiry

Strategy for Business Recovery in NOVO Cinemas

AI in the Public Eye: Investigating Public AI Literacy Through AI Art

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