Artificial Intelligence (AI) plays an increasingly important role in improving HCI and user experience. Yet many challenges persist in designing and innovating valuable human-AI interactions. For example, AI systems can make unpredictable errors, and these errors damage UX and even lead to undesired societal impact. However, HCI routinely grapples with complex technologies and mitigates their unintended consequences. What makes AI different? What makes human-AI interaction appear particularly difficult to design? This paper investigates these questions. We synthesize prior research, our own design and research experience, and our observations when teaching human-AI interaction. We identify two sources of AI's distinctive design challenges: 1) uncertainty surrounding AI's capabilities, 2) AI's output complexity, spanning from simple to adaptive complex. We identify four levels of AI systems. On each level, designers encounter a different subset of the design challenges. We demonstrate how these findings reveal new insights for designers, researchers, and design tool makers in productively addressing the challenges of human-AI interaction going forward.
Background and purpose: Thymol, a major component of thyme and oregano, has medical uses in oral care products as an astringent and antibiotic. Its distinctive sharp odour and pungent flavour are considered aversive properties. The molecular basis of these aversive properties is not well understood. Experimental approach: The ability of thymol to activate human transient receptor potential channel A1 (hTRPA1) expressed in stably transfected human embryonic kidney 293 (HEK293) cells was measured by membrane potential and calcium-sensitive dyes in a fluorescence-imaging plate reader (FLIPR) assay. Direct activation of hTRPA1 currents was measured by whole-cell voltage clamp recording. Intracellular calcium changes were measured using fura-2 dye. The FLIPR assay was also used to measure membrane potential changes elicited by thymol after pretreatment with camphor, a known TRPA1 inhibitor. The ability of related alkyl phenols to activate hTRPA1 was also determined. Key results: Thymol potently activated a membrane potential response and intracellular calcium increase in hTRPA1-expressing HEK293 cells in a concentration-dependent manner. Activation by thymol desensitized hTRPA1 to further exposure to thymol or the known ligand allyl isothiocyanate (AITC). The related phenols 2-tert-butyl-5-methylphenol, 2,6-diisopropylphenol (propofol) and carvacrol also activated hTRPA1. Phenols with less bulky carbon substitutions and lower logP values were less potent in general. The response to thymol was blocked by camphor. Conclusions and implications: These results suggest a role for hTRPA1 activation in the reported pungent and aversive properties of some of these pharmaceutically important phenols.
With progress in enabling autonomous cars to drive safely on the road, it is time to start asking how they should be driving. A common answer is that they should be adopting their users' driving style. This makes the assumption that users want their autonomous cars to drive like they drive -aggressive drivers want aggressive cars, defensive drivers want defensive cars. In this paper, we put that assumption to the test. We find that users tend to prefer a significantly more defensive driving style than their own. Interestingly, they prefer the style they think is their own, even though their actual driving style tends to be more aggressive. We also find that preferences do depend on the specific driving scenario, opening the door for new ways of learning driving style preference.
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