Research Outline

Responsible AI and Workforce Decisions


To have a broad understanding of trust as it specifically relates to the use of AI in Workforce Management. This should be business-oriented and aimed at practical applications, rather than academic or regulatory outputs. An ideal response would include what is already underway, or planned, in the world of data specifically surrounding companies' and organizations' data/AI values, principles, and recommendations to data, AI, and algorithms on the following issues One: Policies, principles, values (e.g., IBM’s public policies, frameworks, values on data usage and AI usage); Two: 2. Recommendations and proposals for data/AI/algorithm policies and stances (for practitioners and for regulators); three: Key studies on data/AI/algorithm policy and principles and approaches; and Four: Any overall key surveys/research pertaining to this. This should be across four verticals: companies (cross-sector), trade Associations, civil society NGOs, and the regulatory landscape. A home run would be a detailed scan that reveals what the current policies, principles, values, recommendations, and research are out there today on this topic. What should NOT be included are what pundits and journalists believe should be in place [opinion pieces].

Early Findings

  • According to a broad new global study of workers by Oracle and Future Workplace, "managers can't compete with artificial intelligence (AI) when it comes to some areas of decision-making and trust building." Among the study's key findings is that "64% of respondents would trust a robot more than their direct manager, and 82% believed AI or bots could perform certain tasks better than their managers. The study surveyed 8,370 HR leaders, managers and employees across 10 countries."
  • The same study also found that AI use is becoming more prominent, as 50% of respondents reported using some form of the technology at work, compared to the 32% who reported using AI in 2018's study.
  • Brookings released a thought piece surrounding protecting privacy in an AI-driven world in early 2020. "This policy brief explores the intersection between AI and the current privacy debate. As Congress considers comprehensive privacy legislation to fill growing gaps in the current checkerboard of federal and state privacy, it will need to consider if or how to address use personal information in artificial intelligence systems. In this brief, I discuss some potential concerns regarding artificial intelligence and privacy, including discrimination, ethical use, and human control, as well as the policy options under discussion."
  • Deloitte published a paper discussing AI in the workplace in March 2020. "Sixty-three percent of the leaders surveyed already view AI as “very” or “critically” important to their business success, and that number is expected to grow to 81% within two years. These leaders see AI rapidly transforming their businesses and industries. Fifty-seven percent predict that AI will “substantially transform” their company within the next three years; two-thirds believe that their industry’s transformation will happen within five years."

Summary Of Our Early Findings Relevant To The Goals

  • As we only have one hour for the initial findings, and based on the fact that the scope of this project, as acknowledged in the client attachment, is quite large, we spent the bulk of the one-hour scanning to ensure that the data required to answer all the questions is available in the public domain, to ensure the data was recent [2019, preferably 2020, and any 2021 data] and to ensure that all areas were at least briefly looked at.
  • Because of this, we did not have a great deal of time to return a great deal of early findings, but we did provide what we think are some relevant and credible findings to be reviewed to be sure we are on the right track.
  • It is of note that during our initial scan, we found nothing of note directly relating to trade associations. Our scoping will reflect this.
  • This will be a global focus. If a more targeted approach is desired, for example, the United States, this would have to be clearly communicated to us in any reply. However, we want to caution that most data is global in nature with specific regions being mentioned. We are suggesting sticking to a global focus unless it is urgent that it only be the United States. This can be clearly communicated to us in any reply by using the comment section next to each scoping. Please do not use the customized option for any comments directly related to specific scopings.
  • Please select one or more of the options provided in the proposed scoping section below.