Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

Artificial Intelligence driven Interaction Design

35 views

Published on

Artificial Intelligence (AI) advances are reframing the challenges and opportunities within Interaction Design. Design as an essence of human fabrication is the key to understand our own existence – Everything we design is designing us in return. We are leaving a time where studies and innovation are needed to define new principles for human-AI interaction. Today is the moment to think about the future of interaction design.

Published in: Design
  • Be the first to comment

  • Be the first to like this

Artificial Intelligence driven Interaction Design

  1. 1. Artificial Intelligence Driven Interaction Design Joana Cerejo, 2019 joana_cerejo@sapo.pt Faculty of Engineering of the University of Porto Doctoral Program in Digital Media The goal of this presentation is to share some thoughts on how Artificial Intelligence is and will impact the Design field. Especially the Interaction Design field. Presenter Notes
  2. 2. HOIA Product Designer & UX Consultant My name is Joana Cerejo and currently I work as a Product Designer. Presenter Notes
  3. 3. HATID I work for Adtalem Global Education. Adtalem Global Education is an American education group. They own several universities and companies. One of them is Becker Professional Education where we developed eLearning software. Currently, we are evolving the business model to a hyper-personalized learning experience throughout features that are supported by Artificial Intelligence, Machine learning, and Deep Learning. Presenter Notes
  4. 4. P.hD. Digital Medias AI ML IoT HCD HCI UX CX Because of my work experience, and realizing in the first person how much AI is impacting Design. I felt the need to seek for a PhD where I could learn and research more about these topics: Presenter Notes
  5. 5. Agenda Context and Motivations Research Purposes Scope So, the presentation will follow three moments: First, Context and Motivations Second, Research Purposes And third the scope that AI is having and will have in the Design field, especially the Interaction Design Field. Presenter Notes
  6. 6. We cannot comprehend the worlds of human experience without design. // Fry 2015 ONTEXT Design is a human fabrication. Design is a human fabrication. For Tony Fry we cannot comprehend the world of human experience without design. Nonetheless, comprehend the dimensions of design is a hard task because… Presenter Notes
  7. 7. ONTEXT Require several knowledge domains and a broad range of skills. Design Problems, Design problems require several knowledge domains and a broad range of skills. Presenter Notes
  8. 8. Technology plays a prodigious role in shaping the future of design. // Dove et al., 2017; Yang et al., 2018; Thébault et al., 2011 ONTEXT Intrinsically, technology has played an important role in the field of design: Both in its creative and creation processes scope. That why, there is a need to investigate and understand better the impact that new technologies have had and will have in the field of design. Presenter Notes
  9. 9. ONTEXT AI ∩ Design Especially in the interception and synergy of Interaction Design and AI. Since we are in the early stages of the transformation of the design field through the intervention of Artificial Intelligence, this is an important moment to objective investigate and understand the consequences and repercussions that this technology is having on how we interact with technology. Presenter Notes
  10. 10. Design problems itself are one of the most complex problems to tackle within Artificial Intelligence (AI). ONTEXTAI ∩ Design // Grecu and Brown 1998 With the interception of this two fields, for Grecu and Brown… So, this means that… Presenter Notes
  11. 11. OTIVATIO AI ∩ Design // Dove et al., 2017; Yang et al., 2018 The touchpoints a designer needs to consider are growing in complexity, especially when AI is spreading around all types of industries. Presenter Notes
  12. 12. OTIVATIO AI ∩ Designer // Dove et al., 2017; Yang et al., 2018 The main challenge of converging design to these technological developments, is the exponential growth of complexity in the process of creation and decision making. There is a need and opportunity here to rethink the designer role within the profession. It is extremely important to understand which will be the demands of the professional requirements in the near future. However, authors such as Dove and Yang argue that designers need to be literate for some basic concepts of data analysis and AI. Presenter Notes
  13. 13. UXD must adapt to AI OTIVATIO These developments in the field of technology and design are demanding a rethinking of current design conventions. Designers, especially digital designers, need to adapt to the current and future scope of AI. However, it is important to realize how comfortable designers are to engage in the creation and development of products or services oriented to this type of technology. Presenter Notes
  14. 14. Time AI-driven technology is promising to enable automation. // Sophie kleber, 2015 ONTEXT Technology User Input According to Sophie Kleber, our interactions have been changing due to technological evolution, and especially thanks to the advanced in the field of Artificial Intelligence. The author explains that with the advances of automation and prediction within technology driven by AI the tendency will be the decay of user input. Presenter Notes
  15. 15. Time More // Sophie kleber, 2015 Automation Anticipation Streamlining Service Technology Intelligent Network ONTEXT Technology User Input Therefore, with these advances we will have more: Presenter Notes
  16. 16. Time Less // Sophie kleber, 2015 Cognitive overload Paradox of choice Decision fatigue Technologic anxiety Screen interaction ONTEXT Technology User Input And less: Presenter Notes
  17. 17. How will we design usable and delightful experiences for AI- driven services? Research Purposes What's important to retain here, is how designers will design the line that balances anticipation and automation in their designs. It is imperative that products and services always provide people with the ability to regain control over the system so that they can reverse a decision that the system may have made on behalf of them. How to project to these contexts raise several problems, doubts and challenges. Presenter Notes
  18. 18. ESEARC Assurance & Trust Design Process Users & Designers AI In order to understand holistically the impact that AI is having and will have in the Design field. We can organize the problematics in three research areas. The great challenge now in the design field is to understand how we will project trust and control by being transparent and honest in what we create. And understand the implications of decision- making processes on AI- oriented products and services. Presenter Notes
  19. 19. ESEARC Assurance & Trust Ethics Cognitive BiasTransparency Serendipity
  20. 20. Assurance & Trust How will designers be able to improve the trust of AI-driven Services? ESEARC
  21. 21. Assurance & Trust How will designers be able to design transparent systems? ESEARC
  22. 22. Assurance & Trust How a Human-centered design process will elevate AI-driven services? ESEARC
  23. 23. Assurance & Trust What will be the cost of failing? ESEARC
  24. 24. Assurance & Trust What becomes of the human experience if decisions are made for us? (discover and serendipity) ESEARC
  25. 25. ESEARC Design Process Methodologies Process Tools Teams Decision-making
  26. 26. Design Process How does a customer journey map look like in an AI-driven service? ESEARC
  27. 27. Design Process Will the current interview techniques continue to work? ESEARC
  28. 28. Design Process How content strategy will be developed for automated or predictive systems? ESEARC
  29. 29. Design Process Will personas still be an effective model for understanding user needs on predictive systems? ESEARC
  30. 30. Design Process How will design research support the decision-making process of AI-driven services? ESEARC
  31. 31. ESEARC Users & Designers AI as a design material Usability Frameworks Data
  32. 32. Users & Designers How can we leverage AI as a design material? ESEARC
  33. 33. Users & Designers Are designers falling to anticipate AI opportunities in their practice? ESEARC
  34. 34. Users & Designers Can designers work with a material they do not fully comprehend? ESEARC
  35. 35. Users & Designers How will designers and data scientists communicating their ideas better with each other? ESEARC
  36. 36. Users & Designers How can we successfully design wireframes for hyper-personalized applications? ESEARC
  37. 37. Users & Designers What skills and knowledge will designers need to pivot, adapt, and thrive in AI-driven services? ESEARC
  38. 38. Users & Designers How AI will touch the user flow of a designer? ESEARC
  39. 39. New models are needed to design within AI and IoT. // Marenko and Allen, 2016 It is time to rethink the standards of Human-centered Design, Human-computer Interaction inside AI and IoT. COP
  40. 40. User-centered Design HypothesisUser Insights COP So far, the designer gathers ideas from the users insights: Presenter Notes
  41. 41. Big Data User Insights COP Hypothesis With the growth and abundance of data, we may be witnessing a shift in this paradigm. Presenter Notes
  42. 42. We are shifting from … // Girardin and Lathia, 2017 Formulating research questions based on user’s needs Formulating research questions that arise from the current availability of data - surveys - interviews - focus groups - direct observation - data analysis - Business intelligence - Pattern recognition COP This means that the designer has the advantage of not only being able to formulate questions and hypotheses from the user's perspective; through surveys, interviews, focus groups and field observation; as well as formulate questions and hypotheses through standards and data from "Big Data". Presenter Notes
  43. 43. Hypothesis // Dove et al., 2017 “Designers do not know how to bring their UXD expertise to bear on AI”. COP There is a whole new world of assumptions that designers can use to produce useful solutions or goods with other types of added value for users. However, some authors argue that in general designers are not prepared for these new models. Presenter Notes
  44. 44. The center of design is now an organic and unpredictable evolving system. // Van Allen, 2017; Dove et al., 2017; Fischer, 2002 Static Living Ecosystem COP These authors argue that the interaction will be dictated by temporal fragments, in the sense of: pre-interaction, interaction and post-interaction. Thus, we are dealing with the evolution of design in the sense that it goes from a static convention to an emerging living ecosystem. Presenter Notes
  45. 45. Pre-interaction Interaction Post-interaction COP Designing solutions for "Pre- interaction" will require design methods like Anticipatory Design. Anticipatory Design principle focused on the simplification of interactions presented to users - Invisible Interactions. Thus, Anticipatory design, is a principle that moves around: - Learn - Predict - To anticipate Presenter Notes
  46. 46. VS Automation Users Input AI has the potential to amplify the human experience. But to move on in this direction, designers face the challenge of designing designs that anticipate and understand the line that separates automation versus what decisions users will always want to make. Presenter Notes
  47. 47. VS Automation Users Input TRUST For designers, this line will be the key to designing solutions that understand what level of trust and automation users are willing to delegate (in the decision- making steps) to services considered "smart". It is in this new context that designers need to gain new skills in how to consciously design transparent systems so that users feel in control under the technology. Presenter Notes
  48. 48. Anticipatory Design is a new approach in design, where decisions are designed to anticipate decisions on behalf of the user. The premise behind this method is to remove the need for choices and reduce the cognitive load by letting the system to make tasks and decisions on behalf of the user. // Van Bodegraven, 2017; Zamenopoulos and Alexiou, 2007; Clark, 2016 One of the main focuses of my research is on Anticipatory Design. This new design model is key for the Pre-interaction frame time presented previously. The term "Anticipation" is not new, it is present in various areas and sciences. However, what this new concept within design proposes is to create standards or standards behaviors to design solutions for services focused on AI and ML. So, as the slide indicates: Presenter Notes
  49. 49. It is output, without much need for input. It is about leveraging past choices to predict future decisions. // Miklos Philips, 2017 COP Anticipatory Design follows the premise that future systems will be able to efficiently anticipate and make decisions and / or tasks on behalf its users. Act without user input. Presenter Notes
  50. 50. Design (Anticipatory Design) AI IoT UX COP his method exists through the conjunction of AI (through machine learning and data analysis), Internet of Things and User Experience Design. This conjunction is shaping the way we design and experience products and services. This principle is having an impact on the process of creation and decision making within the design process. Presenter Notes
  51. 51. Anticipatory Design implies 1. Data will be the foundation of every service 2. AI will simplify the most complex decisions 3. Most users interactions will become obsolete 4. Privacy will change its meanings COP Point 1 - With the paradigm shift within design: Data will be the basis of support and crucial factor to support the development of any service based on Anticipatory Design. Point 2 - This method will be the tool to create solutions and standards that do not require the direct involvement of its users Point 3 - As advocated by Shapio (2015) (…) Point 4 - There is no Artificial Intelligence without data and for there to be data the norms to collect them will force the rethinking of the current privacy policies Presenter Notes
  52. 52. Conclusion The premise of Anticipatory design is not to help the user to make a decision, but rather to create an ecosystem where there is no need for a decision to be made - this happens automatically and without user interaction. // Shapio, 2015
  53. 53. Dove, Graham, Kim Halskov, Jodi Forlizzi, and John Zimmerman. 2017. “UX Design Innovation.” In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems - CHI ’17, 278–88. https://doi.org/10.1145/3025453.3025739. Fry, Tony. 2015. “Whither Design / Whether History.” In Design and the Question of History, 1st ed., 320. Bloomsbury Academic. Girardin, Fabien, and Neal Lathia. 2017. “When User Experience Designers Partner with Data Scientists.” In Aaai 2017 Spring Symposia, 376–81. Grecu, DL, and DC Brown. 1998. “Dimensions of Machine Learning in Design.” Artificial Intelligence for Engineering Design, Analysis and Manufacturing, no. April: 117–22. http://www.cs.wpi.edu/~dgrecu,%0Ahttp://www.wpi.edu/~dcb%0Ahttp://journals.cambridge.org/production/action/cjoGetFulltext? fulltextid=38612. Hebron, Patrick. 2016. Machine Learning for Designers. Edited by Angela Rufino. 1st ed. O’Reilly Media, Inc. Marenko, Betti, and Philip van Allen. 2016. “Animistic Design: How to Reimagine Digital Interaction between the Human and the Nonhuman.” Digital Creativity 27 (1): 52–70. https://doi.org/10.1080/14626268.2016.1145127. Shapio, Aaron. 2015. “The Next Big Thing In Design? Less Choice.” 2015. https://www.fastcompany.com/3045039/the-next-big-thing-in-design-fewer-choices. Thébault, Pierrick, Henri Samier, David Bihanic, Lille Nord De France, and Le Mont-houy. 2011. “Designing for the Ubiquitous Computing Era : Towards the Reinvention of Everyday Objects and the Creation of New User Experiences.” International Journal of Design and Innovation Research X: 1–25. Yang, Qian, Alex Scuito, John Zimmerman, Jodi Forlizzi, and Aaron Steinfeld. 2018. “Investigating How Experienced UX Designers Effectively Work with Machine Learning.” In Proceedings of the 2018 on Designing Interactive Systems Conference 2018 - DIS ’18, 585–96. https://doi.org/ 10.1145/3196709.3196730. EFERENCE
  54. 54. Thank you.

×