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How to make good use of AI technologies? @ Tsukuba Conference 2021

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How to Make Good Use of AI Technologies


Clarifying the Boundary between Humans and Machines
2021.09.30
Hiromu Yakura


U...

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2
• Hiromu Yakura


• Ph.D. student at University of Tsukuba


• Google Ph.D. Fellow (2020)


• Research area: Human-Compu...

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How to Make Good Use of AI Technologies


Clarifying the Boundary between Humans and Machines
2021.09.30
Hiromu Yakura


U...

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How to make good use of AI technologies? @ Tsukuba Conference 2021

  1. 1. How to Make Good Use of AI Technologies Clarifying the Boundary between Humans and Machines 2021.09.30 Hiromu Yakura University of Tsukuba Tsukuba Conference
  2. 2. 2 • Hiromu Yakura • Ph.D. student at University of Tsukuba • Google Ph.D. Fellow (2020) • Research area: Human-Computer Interaction • HCI is an interdisciplinary fi eld that 
 explores new ways of using computers. • What HCI has invented: mouse, multitouch interface, etc. • Particularly, my research question is: Self-Introduction @hiromu1996 How we can make a human-centric use of AI technology 
 that is imperfect and often makes a mistake?
  3. 3. How to Make Good Use of AI Technologies Clarifying the Boundary between Humans and Machines 2021.09.30 Hiromu Yakura University of Tsukuba Tsukuba Conference
  4. 4. How to Make Bad Use of AI Technologies Clarifying the Boundary between Humans and Machines 2021.09.30 Hiromu Yakura University of Tsukuba Tsukuba Conference
  5. 5. Robust Audio Adversarial Example for a Physical Attack Hiromu Yakura*†, Jun Sakuma*† * University of Tsukuba, Japan 
 † RIKEN Center for Arti fi cial Intelligence Project, Japan IJCAI 2020
  6. 6. Background: Risk of abusing AI using adversarial example 6 • It is known that we can mislead AI models by intentionally adding a small noise to the inputs. • In this case, the right image is classi fi ed as a gibbon. Using this adversarial example, we can abuse 
 AI-based systems without being noticed by humans. Goodfellow, I. J., Shlens, J., & Szegedy, C.: Explaining and harnessing adversarial examples. In Proc. of ICLR. (2015)
  7. 7. Background: Risk of abusing AI using adversarial example 7 • The risk of such an attack is not limited to images, 
 but also to speech recognition. • In particular, speech recognition is widely used 
 in the form such as Siri or Google Home. However, abusing speech recognition in the real world has been considered di ffi cult due to reverberation. [Carlini+, 2018] • If we can mislead speech recognition models to transcribe speci fi c words, such voice assistants can also be abused. Carlini, N., & Wagner, D.: Audio Adversarial Examples: Targeted Attacks on Speech-to-Text. In Proc. of Deep Learning and Security Workshop. (2018)
  8. 8. • In a listening experiment involving 50 participants, 
 we con fi rmed no one could tell these hidden messages. 8 Proposal: Robust attack for speech recognition We realized such an attack in the real world 
 via a new method that simulates reverberation. Original audio "hello world" "open the door" Manipulated audio transcribed as
  9. 9. Generate (non-software) Bugs to Fool Classi fi ers Hiromu Yakura*†, Youhei Akimoto*†, Jun Sakuma*† * University of Tsukuba, Japan 
 † RIKEN Center for Arti fi cial Intelligence Project, Japan AAAI 2020
  10. 10. Proposal: Attacking self-driving cars with moth-like stickers S. Chen, et al. Shapeshifter: Robust physical adversarial attack on faster RCNN object detector. ECML PKDD 2018. • This mechanism is also applicable to deceive self-driving cars. • What if the cars recognize a STOP sign as Speed 80? • This example can cause such a mistake 
 but looks too suspicious not to be noticed by humans. 10 [Chen+, '18] Proposed We showed that these moth-like stickers can mislead 
 AI models without making humans feel suspicious.
  11. 11. How to Make Good Use of AI Technologies Clarifying the Boundary between Humans and Machines 2021.09.30 Hiromu Yakura University of Tsukuba Tsukuba Conference
  12. 12. 12 Basic idea: How to overcome the imperfection of AI models No matter how much technical improvement we make, 
 AI-based systems will make mistakes. • AI models just perform inference based on the trends 
 they found in the data given in advance. • Thus, we can't deny the possibility of their mistakes, 
 even if we don't intentionally attack them. Find situations even such imperfect models are beneficial!
  13. 13. 13 Basic idea: The importance of understanding humans • It may sound like humanities or sociology 🤔 
 but clarifying the area that humans are not good at is crucial. Observe humans and gain a deeper understanding of humans! Humans are 
 not good at good at AI models are 
 good at not good at Not so bene cial Frustrating Sweet spots Intractable
  14. 14. REsCUE: A framework for 
 REal-time feedback on behavioral CUEs 
 using multimodal anomaly detection Riku Arakawa† and Hiromu Yakura‡ 
 (equal contribution) † The University of Tokyo, Japan ‡ University of Tsukuba, Japan ACM CHI 2019 @ Glasgow, UK
  15. 15. Background: Limitation of current conversation analysis 15 • In executive coaching, coaches are required to observe 
 nonverbal cues of a client consistently while they are talking. • AI models that can estimate the emotions of humans would 
 be helpful for supporting coaches. • However, professional coaches felt 
 the models are useless and frustrating. • The meaning of nonverbal behaviors 
 largely depends on individuals and contexts. I. Damian, et al. Augmenting Social Interactions: Realtime Behavioural Feedback using Social Signal Processing Techniques. ACM CHI 2015. <%BNJBO
  16. 16. Proposal: Separating observation and interpretation 16 Humans AI models • AI models detect nonverbal signals from a constant perspective. • Humans interpret their meaning considering the context. Separating observation and interpretation can enable 
 a better collaboration of humans and AI models. 👎 understand contexts of humans 👍 understand contexts 👎 maintain consistent observation 👍 exhibit constant performance
  17. 17. Proposal: Interpretable detection of nonverbal signals 17 • AI-based system detects when the client exhibits 
 a sudden change in their behavior and visualizes it. Representative states Changes in nonverbal behavior This system is designed to help 
 humans show the best performance 
 in the area they are good at.
  18. 18. 18 Basic idea: The importance of understanding humans Humans are 
 not good at good at AI models are 
 good at not good at Not so bene cial Frustrating Sweet spots Intractable
  19. 19. 19 Advanced idea: Frustrations teaches success Humans are 
 not good at good at AI models are 
 good at not good at Not so bene cial Frustrating Sweet spots Intractable Investigating why humans are frustrated against technologies provides implications for the direction of improvement.
  20. 20. 🤝 No More Handshaking 🙅 How have COVID-19 pushed the expansion of 
 computer-mediated communication in Japanese idol culture? Hiromu Yakura University of Tsukuba, Japan ACM CHI 2021 20
  21. 21. COVID-19 has forced Japanese idol groups 
 to halt their meet-and-greet events. akushukai 
 (handshaking event) The photo is taken from Wikimedia Commons under the CC-BY-SA 2.0 license: https://w.wiki/3AF4 These events have played a key role in their marketing strategy to cultivate fans’ loyalty Instead, most idol groups have migrated to computer-mediated communication (CMC). 21
  22. 22. One common approach was online one-on-one sessions. Fans who purchased a CD are allowed to 
 talk to a member via a video call. 22
  23. 23. Emergent forms of online meet-and-greet events The image is taken from a YouTube video only for presentation purpose: https://www.youtube.com/watch?v=6yOxmVoAE14 Fans were not allowed to get closer than four meters to members. Instead, they can talk via a video call using a pair of iPads. On-site online one-on-one event 23
  24. 24. Why did fans gather in the venue to talk via iPad? There is something available in this event but not available when they join a video call from their home. This teaches that what HCI researchers should do is: 24 Aura: the unique existence of a work of art 
 at the place where it happens to be Even the most perfect reproduction lacks [it] Walter Benjamin 
 (1892-1940) 🙅 Improve the reproduction quality 🙆 Develop new channels that deliver the unique existence
  25. 25. How to Make Good Use of AI Technologies Clarifying the Boundary between Humans and Machines • Observe humans and gain a deeper understanding to 
 fi nd sweet spots where AI-based systems are bene fi cial • This approach simultaneously provides 
 a new perspective of understanding humans. 
 • Finding ways to make good use of AI technologies can be 
 a re fl ective process questioning our identity.

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