Reptes i responsabilitats del disseny d’UX en models d’IA de text a imatge: Discussió a través d’una avaluació heurística comparativa
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El ràpid avenç i l’adopció de la IA generativa en àmbits creatius i professionals marquen una evolució significativa en la interacció tecnològica i plantegen debats fonamentals sobre la seva integració i usabilitat i sobre el seu impacte social més ampli. Aquest article aprofundeix en els múltiples reptes i habilitats que la IA generativa presenta, centrant-se en concret en les eines de conversió de text a imatge i la seva integració en les pràctiques laborals quotidianes d’artistes, dissenyadors, arquitectes i investigadors. A mesura que aquests creadors incorporen a la seva feina la imprevisibilitat i ambigüitat inherents a la IA, es fa imperatiu un examen crític de les seves implicacions ètiques, legislatives i mediambientals. Destaquem que els aspectes relacionats amb l’experiència d’usuari (UX) i la interfície d’usuari (UI) d’aquestes tecnologies revolucionàries continuen estant majoritàriament poc explorats. Jakob Nielsen, pioner de la UX, ha advertit fa poc que els professionals d’aquest camp s’han d’adaptar als ràpids avenços de la IA o es quedaran obsolets per a una indústria que cada vegada és més determinant en l’àmbit creatiu contemporani. Nielsen estableix un paral·lelisme entre l’era actual de la IA i l’auge de les puntcom en els anys noranta i fa palesa la lentitud amb què els professionals de l’experiència d’usuari es van adaptar a internet, que va provocar una pèrdua d’oportunitats i la manca d’un disseny centrat en l’usuari. Com a conseqüència, la usabilitat de les eines d’IA generativa és una preocupació primordial, sobretot perquè els usuaris no experts cada cop utilitzen més aquests sistemes. En aquest article s’analitzen els problemes d’usabilitat, concretament la barrera d’articulació en què els usuaris tenen dificultats per comunicar eficaçment les instruccions a la IA, i la consegüent necessitat d’interfícies més intuïtives i accessibles.
Per mitjà d’una anàlisi comparativa i una avaluació heurística de quatre models capdavanters (Midjourney, Dall-E, Stable Diffusion i Adobe Firefly), que presenta un cas pràctic únic a efectes comparatius gràcies als seus elements divergents d’interfície d’usuari i experiència d’usuari, volem oferir una visió de l’estat actual de les eines d’IA i proposar vies per fer-ne un ús responsable i eficaç.
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Annapaola Vacanti, Università Iuav di Venezia; Elisava, Facultat de Disseny i Enginyeria de Barcelona (UVic-UCC)
Annapaola Vacanti és dissenyadora i becària d’investigació a la Università Iuav di Venezia, i investigadora visitant a Elisava. Treballa en la interacció entre l’ésser humà i la tecnologia, explorant la intersecció entre els factors humans, el desenvolupament tecnològic i l’impacte social i ecològic d’aquest últim. L’any 2022 es va doctorar en Disseny a la Università di Genova. Paral·lelament a la seva carrera acadèmica, des del 2018 és directora artística i organitzadora de TEDxGenova, un esdeveniment autònom que opera sota la llicència oficial TED per a la difusió local d’idees valuoses.
Francesco Burlando, Università di Genova; Elisava, Facultat de Disseny i Enginyeria de Barcelona (UVic-UCC)
Francesco Burlando és dissenyador i becari d’investigació a la Università di Genova, investigador visitant a Elisava i professor visitant de la Beijing University of Chemical Technology. La seva investigació se centra a fomentar el disseny de sistemes tecnològics innovadors i, especialment, la relació entre aquests i els usuaris als quals estan destinats. L’any 2022 es va doctorar a la Università di Genova amb una tesi titulada “Més que humanoides. Pràctiques i eines per al disseny de robots humans*”.
Alejandro Iván Paz Ortiz, Elisava, Facultat de Disseny i Enginyeria de Barcelona (UVic-UCC)
Iván Paz és professor associat a Elisava, Facultat de Disseny i Enginyeria de Barcelona (UVic-UCC). Li agrada investigar com la intersecció entre ciències, arts i humanitats ofereix noves possibilitats creatives. En concret, estudia com interactuem amb els algoritmes d’aprenentatge automàtic i l’ús del codi com a interfície per a la creació en temps real. El seu treball utilitza software i electrònica desenvolupats a mida. Ha col·laborat amb universitats, ha dissenyat sistemes interactius per a festivals i ha presentat obres i actuacions per Amèrica i Europa.
Massimo Menichinelli, Elisava, Facultat de Disseny i Enginyeria de Barcelona (UVic-UCC)
Massimo Menichinelli és professor associat a Elisava, Facultat de Disseny i Enginyeria de Barcelona (UVic-UCC), doctor en Nous Mitjans (Aalto University) i màster en Disseny Industrial (Politecnico di Milano). Des del 2005 investiga i treballa en el paper del disseny en el desenvolupament d’ecosistemes i infraestructures que donen suport a processos col·laboratius, distribuïts i oberts. Investiga com visualitzar i codissenyar processos de disseny, com mesurar l’impacte de les activitats de disseny, com desenvolupar i donar suport a iniciatives d’innovació social i digital, com desenvolupar i investigar plataformes i com promoure la col·laboració i la creació d’ecosistemes entre la universitat i la indústria.
Bandi, A., P. V. S. R. Adapa, and Y. E. V. P. K. Kuchi. 2023. “The power of generative AI: A review of requirements, models, input–output formats, evaluation metrics, and challenges”. Future Internet 15 (8): 260, 1-60. https://doi.org/10.3390/fi15080260
Caramiaux, Baptiste, and Sarah Fdili Alaoui. 2022. “Explorers of Unknown Planets: Practices and Politics of Artificial Intelligence in Visual Arts.” In Proceedings of the ACM on Human-Computer Interaction, vol. 6, issue CSCW2, article 477, 1-24. New York: ACM. https://doi.org/10.1145/3555578
Cattabriga, Andrea, and Vladan Joler. 2023. “Decentering Design With AI”. Diid — Disegno Industriale Industrial Design 80 (12): 10-19. https://doi.org/10.30682/diid8023a
Crawford, Kate. 2021. The Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence. New Haven: Yale University Press.
Crawford, Kate, and Trevor Paglen. 2021. “Excavating AI: The Politics of Images in Machine Learning Training Sets.” AI & Society 36, no. 4: 1105–1116. https://doi.org/10.1007/s00146-021-01162-8
Dove, Graham, Kim Halskov, Jodi Forlizzi, and John Zimmerman. 2017. “UX Design Innovation: Challenges for Working with Machine Learning as a Design Material”. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, 278–288. New York: ACM. https://doi.org/10.1145/3025453.3025739
Green Nudges. n.d. “Promoting greener driving: Google Maps‘ fuel-efficient routes.” Green Nudges. Accessed 03/04/2024. https://www.green-nudges.com/google-maps/
Hintemann, Ralph, and Simon Hinterholzer. 2022. Data centers 2021: Data center boom in Germany continues - Cloud Computing Drives the Growth of the Data Center Industry and Its Energy Consumption. Berlin: Borderstep Institute. https://doi.org/10.13140/RG.2.2.31826.43207
Holmquist, Lars Erik. 2017. "Intelligence on Tap: Artificial Intelligence as a New Design Material." Interactions 24 (4): 28–33. https://doi.org/10.1145/3085571
Lew, Gavin, and Schumacher, Robert M. 2020. AI and UX: Why artificial intelligence needs user experience. New York: Apress.
Luccioni, Alexandra Sasha, Yacine Jernite, and Emma Strubell. 2024. “Power Hungry Processing: Watts Driving the Cost of AI Deployment?”. In FAccT '24: Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency, 85-99. New York: ACM. https://doi.org/10.1145/3630106.3658542
Manovich, Lev and Emanuele Arielli. 2024. “Artificial Aesthetics: Generative AI, art and visual media.” Manovich.net. Accessed 03/04/2024. http://manovich.net/index.php/projects/artificial-aesthetics
Mugunthan, Tarun. 2023. "Overcoming the Articulation Barrier in Generative AI Using Hybrid Interfaces." Nielsen Norman Group. Accessed 02/01/2024. https://www.nngroup.com/articles/ai-articulation-barrier
Nielsen, Jakob. 1994. “Heuristic Evaluation.” In Usability Inspection Methods, edited by Jakob Nielsen and Robert L. Mack. New York: Wiley.
Nielsen, Jakob. 2023a. “ UX Needs a Sense of Urgency About AI.” UX Tigers. Accessed 02/01/2024. https://www.uxtigers.com/post/ux-urgency-ai
Nielsen, Jakob. 2023b. “Classic Usability Important for AI.” UX Tigers. Accessed 03/04/2024. https://www.uxtigers.com/post/classic-usability-ai
Paoletti, Ingrid. 2021. Siate materialisti!. Torino: Einaudi.
Pasquinelli, Matteo, and Vladan Joler. 2021. “The Nooscope Manifested: AI as Instrument of Knowledge Extractivism”. AI & Society 36: 1263–1280. https://doi.org/10.1007/s00146-020-01097-6
Shneiderman, Ben, Catherine Plaisant, Maxine Cohen, Steven Jacobs, and Niklas Elmqvist. 2016. Designing the User Interface: Strategies for Effective Human-Computer Interaction. 6th ed. Boston: Pearson.
Shumailov, Ilia, Zichao Shumaylov, Yiren Zhao, Yarin Gal, Nicolas Papernot, and Ross Anderson. 2023. “Model Dementia: Generated Data Makes Models Forget.” arXiv e-prints, arXiv:2305.17493. https://doi.org/10.48550/arXiv.2305.17493
Thiel, David. 2023. “Identifying and Eliminating CSAM in Generative ML Training Data and Models”. Stanford Digital Repository. https://doi.org/10.25740/kh752sm9123
Wachter, Sandra, Brent Mittelstadt, and Luciano Floridi. 2017. "Transparent, Explainable, and Accountable AI for Robotics." Science Robotics 2: eaan6080. https://doi.org/10.1126/scirobotics.aan6080
Zamfirescu-Pereira, J.D., Richmond Y. Wong, Bjoern Hartmann, and Qian Yang. 2023. “Why Johnny Can’t Prompt: How Non-AI Experts Try (and Fail) to Design LLM Prompts.” In CHI '23: Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, article 437, 1–21. New York: ACM. https://doi.org/10.1145/3544548.3581388
Bandi, A., P. V. S. R. Adapa, and Y. E. V. P. K. Kuchi. 2023. “The power of generative AI: A review of requirements, models, input–output formats, evaluation metrics, and challenges”. Future Internet 15 (8): 260, 1-60. https://doi.org/10.3390/fi15080260
Caramiaux, Baptiste, and Sarah Fdili Alaoui. 2022. “Explorers of Unknown Planets: Practices and Politics of Artificial Intelligence in Visual Arts.” In Proceedings of the ACM on Human-Computer Interaction, vol. 6, issue CSCW2, article 477, 1-24. New York: ACM. https://doi.org/10.1145/3555578
Cattabriga, Andrea, and Vladan Joler. 2023. “Decentering Design With AI”. Diid — Disegno Industriale Industrial Design 80 (12): 10-19. https://doi.org/10.30682/diid8023a
Crawford, Kate. 2021. The Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence. New Haven: Yale University Press.
Crawford, Kate, and Trevor Paglen. 2021. “Excavating AI: The Politics of Images in Machine Learning Training Sets.” AI & Society 36, no. 4: 1105–1116. https://doi.org/10.1007/s00146-021-01162-8
Dove, Graham, Kim Halskov, Jodi Forlizzi, and John Zimmerman. 2017. “UX Design Innovation: Challenges for Working with Machine Learning as a Design Material”. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, 278–288. New York: ACM. https://doi.org/10.1145/3025453.3025739
Green Nudges. n.d. “Promoting greener driving: Google Maps‘ fuel-efficient routes.” Green Nudges. Accessed 03/04/2024. https://www.green-nudges.com/google-maps/
Hintemann, Ralph, and Simon Hinterholzer. 2022. Data centers 2021: Data center boom in Germany continues - Cloud Computing Drives the Growth of the Data Center Industry and Its Energy Consumption. Berlin: Borderstep Institute. https://doi.org/10.13140/RG.2.2.31826.43207
Holmquist, Lars Erik. 2017. "Intelligence on Tap: Artificial Intelligence as a New Design Material." Interactions 24 (4): 28–33. https://doi.org/10.1145/3085571
Lew, Gavin, and Schumacher, Robert M. 2020. AI and UX: Why artificial intelligence needs user experience. New York: Apress.
Luccioni, Alexandra Sasha, Yacine Jernite, and Emma Strubell. 2024. “Power Hungry Processing: Watts Driving the Cost of AI Deployment?”. In FAccT '24: Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency, 85-99. New York: ACM. https://doi.org/10.1145/3630106.3658542
Manovich, Lev and Emanuele Arielli. 2024. “Artificial Aesthetics: Generative AI, art and visual media.” Manovich.net. Accessed 03/04/2024. http://manovich.net/index.php/projects/artificial-aesthetics
Mugunthan, Tarun. 2023. "Overcoming the Articulation Barrier in Generative AI Using Hybrid Interfaces." Nielsen Norman Group. Accessed 02/01/2024. https://www.nngroup.com/articles/ai-articulation-barrier
Nielsen, Jakob. 1994. “Heuristic Evaluation.” In Usability Inspection Methods, edited by Jakob Nielsen and Robert L. Mack. New York: Wiley.
Nielsen, Jakob. 2023a. “ UX Needs a Sense of Urgency About AI.” UX Tigers. Accessed 02/01/2024. https://www.uxtigers.com/post/ux-urgency-ai
Nielsen, Jakob. 2023b. “Classic Usability Important for AI.” UX Tigers. Accessed 03/04/2024. https://www.uxtigers.com/post/classic-usability-ai
Paoletti, Ingrid. 2021. Siate materialisti!. Torino: Einaudi.
Pasquinelli, Matteo, and Vladan Joler. 2021. “The Nooscope Manifested: AI as Instrument of Knowledge Extractivism”. AI & Society 36: 1263–1280. https://doi.org/10.1007/s00146-020-01097-6
Shneiderman, Ben, Catherine Plaisant, Maxine Cohen, Steven Jacobs, and Niklas Elmqvist. 2016. Designing the User Interface: Strategies for Effective Human-Computer Interaction. 6th ed. Boston: Pearson.
Shumailov, Ilia, Zichao Shumaylov, Yiren Zhao, Yarin Gal, Nicolas Papernot, and Ross Anderson. 2023. “Model Dementia: Generated Data Makes Models Forget.” arXiv e-prints, arXiv:2305.17493. https://doi.org/10.48550/arXiv.2305.17493
Thiel, David. 2023. “Identifying and Eliminating CSAM in Generative ML Training Data and Models”. Stanford Digital Repository. https://doi.org/10.25740/kh752sm9123
Wachter, Sandra, Brent Mittelstadt, and Luciano Floridi. 2017. "Transparent, Explainable, and Accountable AI for Robotics." Science Robotics 2: eaan6080. https://doi.org/10.1126/scirobotics.aan6080
Zamfirescu-Pereira, J.D., Richmond Y. Wong, Bjoern Hartmann, and Qian Yang. 2023. “Why Johnny Can’t Prompt: How Non-AI Experts Try (and Fail) to Design LLM Prompts.” In CHI '23: Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, article 437, 1–21. New York: ACM. https://doi.org/10.1145/3544548.3581388
Bandi, A., P. V. S. R. Adapa, and Y. E. V. P. K. Kuchi. 2023. “The power of generative AI: A review of requirements, models, input–output formats, evaluation metrics, and challenges”. Future Internet 15 (8): 260, 1-60. https://doi.org/10.3390/fi15080260
Caramiaux, Baptiste, and Sarah Fdili Alaoui. 2022. “Explorers of Unknown Planets: Practices and Politics of Artificial Intelligence in Visual Arts.” In Proceedings of the ACM on Human-Computer Interaction, vol. 6, issue CSCW2, article 477, 1-24. New York: ACM. https://doi.org/10.1145/3555578
Cattabriga, Andrea, and Vladan Joler. 2023. “Decentering Design With AI”. Diid — Disegno Industriale Industrial Design 80 (12): 10-19. https://doi.org/10.30682/diid8023a
Crawford, Kate. 2021. The Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence. New Haven: Yale University Press.
Crawford, Kate, and Trevor Paglen. 2021. “Excavating AI: The Politics of Images in Machine Learning Training Sets.” AI & Society 36, no. 4: 1105–1116. https://doi.org/10.1007/s00146-021-01162-8
Dove, Graham, Kim Halskov, Jodi Forlizzi, and John Zimmerman. 2017. “UX Design Innovation: Challenges for Working with Machine Learning as a Design Material”. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, 278–288. New York: ACM. https://doi.org/10.1145/3025453.3025739
Green Nudges. n.d. “Promoting greener driving: Google Maps‘ fuel-efficient routes.” Green Nudges. Accessed 03/04/2024. https://www.green-nudges.com/google-maps/
Hintemann, Ralph, and Simon Hinterholzer. 2022. Data centers 2021: Data center boom in Germany continues - Cloud Computing Drives the Growth of the Data Center Industry and Its Energy Consumption. Berlin: Borderstep Institute. https://doi.org/10.13140/RG.2.2.31826.43207
Holmquist, Lars Erik. 2017. "Intelligence on Tap: Artificial Intelligence as a New Design Material." Interactions 24 (4): 28–33. https://doi.org/10.1145/3085571
Lew, Gavin, and Schumacher, Robert M. 2020. AI and UX: Why artificial intelligence needs user experience. New York: Apress.
Luccioni, Alexandra Sasha, Yacine Jernite, and Emma Strubell. 2024. “Power Hungry Processing: Watts Driving the Cost of AI Deployment?”. In FAccT '24: Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency, 85-99. New York: ACM. https://doi.org/10.1145/3630106.3658542
Manovich, Lev and Emanuele Arielli. 2024. “Artificial Aesthetics: Generative AI, art and visual media.” Manovich.net. Accessed 03/04/2024. http://manovich.net/index.php/projects/artificial-aesthetics
Mugunthan, Tarun. 2023. "Overcoming the Articulation Barrier in Generative AI Using Hybrid Interfaces." Nielsen Norman Group. Accessed 02/01/2024. https://www.nngroup.com/articles/ai-articulation-barrier
Nielsen, Jakob. 1994. “Heuristic Evaluation.” In Usability Inspection Methods, edited by Jakob Nielsen and Robert L. Mack. New York: Wiley.
Nielsen, Jakob. 2023a. “ UX Needs a Sense of Urgency About AI.” UX Tigers. Accessed 02/01/2024. https://www.uxtigers.com/post/ux-urgency-ai
Nielsen, Jakob. 2023b. “Classic Usability Important for AI.” UX Tigers. Accessed 03/04/2024. https://www.uxtigers.com/post/classic-usability-ai
Paoletti, Ingrid. 2021. Siate materialisti!. Torino: Einaudi.
Pasquinelli, Matteo, and Vladan Joler. 2021. “The Nooscope Manifested: AI as Instrument of Knowledge Extractivism”. AI & Society 36: 1263–1280. https://doi.org/10.1007/s00146-020-01097-6
Shneiderman, Ben, Catherine Plaisant, Maxine Cohen, Steven Jacobs, and Niklas Elmqvist. 2016. Designing the User Interface: Strategies for Effective Human-Computer Interaction. 6th ed. Boston: Pearson.
Shumailov, Ilia, Zichao Shumaylov, Yiren Zhao, Yarin Gal, Nicolas Papernot, and Ross Anderson. 2023. “Model Dementia: Generated Data Makes Models Forget.” arXiv e-prints, arXiv:2305.17493. https://doi.org/10.48550/arXiv.2305.17493
Thiel, David. 2023. “Identifying and Eliminating CSAM in Generative ML Training Data and Models”. Stanford Digital Repository. https://doi.org/10.25740/kh752sm9123
Wachter, Sandra, Brent Mittelstadt, and Luciano Floridi. 2017. "Transparent, Explainable, and Accountable AI for Robotics." Science Robotics 2: eaan6080. https://doi.org/10.1126/scirobotics.aan6080
Zamfirescu-Pereira, J.D., Richmond Y. Wong, Bjoern Hartmann, and Qian Yang. 2023. “Why Johnny Can’t Prompt: How Non-AI Experts Try (and Fail) to Design LLM Prompts.” In CHI '23: Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, article 437, 1–21. New York: ACM. https://doi.org/10.1145/3544548.3581388
Bandi, A., P. V. S. R. Adapa, and Y. E. V. P. K. Kuchi. 2023. “The power of generative AI: A review of requirements, models, input–output formats, evaluation metrics, and challenges”. Future Internet 15 (8): 260, 1-60. https://doi.org/10.3390/fi15080260
Caramiaux, Baptiste, and Sarah Fdili Alaoui. 2022. “Explorers of Unknown Planets: Practices and Politics of Artificial Intelligence in Visual Arts.” In Proceedings of the ACM on Human-Computer Interaction, vol. 6, issue CSCW2, article 477, 1-24. New York: ACM. https://doi.org/10.1145/3555578
Cattabriga, Andrea, and Vladan Joler. 2023. “Decentering Design With AI”. Diid — Disegno Industriale Industrial Design 80 (12): 10-19. https://doi.org/10.30682/diid8023a
Crawford, Kate. 2021. The Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence. New Haven: Yale University Press.
Crawford, Kate, and Trevor Paglen. 2021. “Excavating AI: The Politics of Images in Machine Learning Training Sets.” AI & Society 36, no. 4: 1105–1116. https://doi.org/10.1007/s00146-021-01162-8
Dove, Graham, Kim Halskov, Jodi Forlizzi, and John Zimmerman. 2017. “UX Design Innovation: Challenges for Working with Machine Learning as a Design Material”. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, 278–288. New York: ACM. https://doi.org/10.1145/3025453.3025739
Green Nudges. n.d. “Promoting greener driving: Google Maps‘ fuel-efficient routes.” Green Nudges. Accessed 03/04/2024. https://www.green-nudges.com/google-maps/
Hintemann, Ralph, and Simon Hinterholzer. 2022. Data centers 2021: Data center boom in Germany continues - Cloud Computing Drives the Growth of the Data Center Industry and Its Energy Consumption. Berlin: Borderstep Institute. https://doi.org/10.13140/RG.2.2.31826.43207
Holmquist, Lars Erik. 2017. "Intelligence on Tap: Artificial Intelligence as a New Design Material." Interactions 24 (4): 28–33. https://doi.org/10.1145/3085571
Lew, Gavin, and Schumacher, Robert M. 2020. AI and UX: Why artificial intelligence needs user experience. New York: Apress.
Luccioni, Alexandra Sasha, Yacine Jernite, and Emma Strubell. 2024. “Power Hungry Processing: Watts Driving the Cost of AI Deployment?”. In FAccT '24: Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency, 85-99. New York: ACM. https://doi.org/10.1145/3630106.3658542
Manovich, Lev and Emanuele Arielli. 2024. “Artificial Aesthetics: Generative AI, art and visual media.” Manovich.net. Accessed 03/04/2024. http://manovich.net/index.php/projects/artificial-aesthetics
Mugunthan, Tarun. 2023. "Overcoming the Articulation Barrier in Generative AI Using Hybrid Interfaces." Nielsen Norman Group. Accessed 02/01/2024. https://www.nngroup.com/articles/ai-articulation-barrier
Nielsen, Jakob. 1994. “Heuristic Evaluation.” In Usability Inspection Methods, edited by Jakob Nielsen and Robert L. Mack. New York: Wiley.
Nielsen, Jakob. 2023a. “ UX Needs a Sense of Urgency About AI.” UX Tigers. Accessed 02/01/2024. https://www.uxtigers.com/post/ux-urgency-ai
Nielsen, Jakob. 2023b. “Classic Usability Important for AI.” UX Tigers. Accessed 03/04/2024. https://www.uxtigers.com/post/classic-usability-ai
Paoletti, Ingrid. 2021. Siate materialisti!. Torino: Einaudi.
Pasquinelli, Matteo, and Vladan Joler. 2021. “The Nooscope Manifested: AI as Instrument of Knowledge Extractivism”. AI & Society 36: 1263–1280. https://doi.org/10.1007/s00146-020-01097-6
Shneiderman, Ben, Catherine Plaisant, Maxine Cohen, Steven Jacobs, and Niklas Elmqvist. 2016. Designing the User Interface: Strategies for Effective Human-Computer Interaction. 6th ed. Boston: Pearson.
Shumailov, Ilia, Zichao Shumaylov, Yiren Zhao, Yarin Gal, Nicolas Papernot, and Ross Anderson. 2023. “Model Dementia: Generated Data Makes Models Forget.” arXiv e-prints, arXiv:2305.17493. https://doi.org/10.48550/arXiv.2305.17493
Thiel, David. 2023. “Identifying and Eliminating CSAM in Generative ML Training Data and Models”. Stanford Digital Repository. https://doi.org/10.25740/kh752sm9123
Wachter, Sandra, Brent Mittelstadt, and Luciano Floridi. 2017. "Transparent, Explainable, and Accountable AI for Robotics." Science Robotics 2: eaan6080. https://doi.org/10.1126/scirobotics.aan6080
Zamfirescu-Pereira, J.D., Richmond Y. Wong, Bjoern Hartmann, and Qian Yang. 2023. “Why Johnny Can’t Prompt: How Non-AI Experts Try (and Fail) to Design LLM Prompts.” In CHI '23: Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, article 437, 1–21. New York: ACM. https://doi.org/10.1145/3544548.3581388