ABSTRACT
This chapter explores trustworthiness in AI and penetrates the black-box opacity through explainable, fair, and ethical AI solutions. AI remains a spirited topic within academic, government, and industrial literature. Much has occurred since the last AI winter in the early 1990's;yet, numerous sources indicate the initial successes solving problems like computer vision, speech recognition, and natural sciences may wane — plunging AI into another winter. Many factors contributed to advances in AI: more data science courses in universities producing data-science capable graduates, high venture capital funding levels encouraging startups, and a decade of broadening awareness among corporate executives about AI promises, real or perceived. Nonetheless, could sources like Gartner be right? Are we approaching another AI winter? As the world learned during the COVID-19 pandemic, when we find ourselves in a crisis, focusing on the fundamentals can have a powerful effect to easing the troubles. As AI makes history, it relies on progress from other domains such as data availability, computing power, and algorithmic advances. Balance among elements maintains a healthy system. AI is no different. Too much or too little of any elemental capability can slow down overall progress. This chapter integrates fundamental ideas from psychology (heuristics and bias), mindfulness in modeling (conceptual models in group settings), and inference (both classical and contemporary). Practitioners may find the techniques proposed in this chapter useful next steps in AI evolution aimed at understanding human behavior. The techniques we discuss can protect against negative impacts resulting from a future AI winter through proper preparation: appreciating the fundamentals, understanding AI assumptions and limitations, and approaching AI assurance in a mindful manner as it evolves. This chapter will address the fundamentals in a unifying example focused on healthcare, with opportunities for trustworthy AI that is impartial, fair, and unbiased. © 2023 Elsevier Inc. All rights reserved.
ABSTRACT
Introduction: Limited research is available regarding vaccine attitudes among students in higher education. While pharmacy students play a vital role in vaccine administration, little is known about their attitudes toward vaccination. The Vaccine Confidence Scale (VCS) is a validated scoring system, ranging 0-10 to quantify general confidence, including subscales for harms, benefits, and trust related to vaccination. Research Question or Hypothesis: To characterize vaccine confidence regarding COVID-19 vaccines in a University population and compare VCS between pharmacy and other students. Study Design: Cross sectional quantitative survey of COVID-19 Vaccine confidence Methods: A survey regarding vaccine confidence was available to Drake University's population from January to February 2021 (Phase 1a/1b of vaccine availability). Participants were recruited biweekly through campus-wide email announcements. The survey consisted of 26 questions related to demographics, VCS, and COVID-19 experiences. VCS and subscales were tabulated. Comparisons were conducted in SPSS v25 using ANOVA, t-tests, or chi-square. Results: Response rate was ~26%. There were 1184 completed surveys;139 (11.8%) were pharmacy students. Of these, 16.3% had already received at least one dose of a COVID-19 vaccine, 71% planned to receive a COVID-19 vaccine, 7.1% planned not to, and 5.6% were unsure. Mean VCS scores were higher among those that had received or planned to receive a vaccine, than those that were unsure, or would not receive a vaccine (8.88 vs 7.30 vs 5.55, P<0.001). Pharmacy students were more likely than other students to have received or plan to receive a vaccine (96.4% vs 85.2%, P=0.002). VCS was higher among pharmacy students than others (8.71 vs 8.52, P=0.05). Harm and Trust subscores were not different, but Benefits subscores were higher among pharmacy students (9.17 vs 8.79, P<0.001). Conclusion: Vaccine confidence was high at private university early in COVID-19 vaccine rollout. Pharmacy student VCS was slightly higher than other students with higher impact of vaccine benefits.