Review of Public Administration and Management

Responsible Artificial Intelligence in Human Resources Technology: Self-Regulation and Public Policy

Calvino Eco^* Department of Public Administration, University of Modena and Reggio Emilia, Modena, Italy
^*Correspondence: Calvino Eco, Department of Public Administration, University of Modena and Reggio Emilia, Modena, Italy, Email:

Received: 05-Aug-2022, Manuscript No. RPAM-22-17940; Editor assigned: 08-Aug-2022, Pre QC No. RPAM-22-17940 (PQ); , QC No. RPAM-22-17940; Revised: 29-Aug-2022, Manuscript No. RPAM-22-17940 (R); Published: 05-Sep-2022, DOI: 10.35248/2315-7844.22.10.358

Description

Human Resources Technology (HR Tech) is a quickly developing industry that increasingly uses Artificial Intelligence (AI) to power software and hardware solutions that help HR specialists and automate and improve Human Resources Management (HRM)-related functions such employee payroll and benefits, recruitment/talent acquisition and management, performance assessment, as well as re-skilling and up-skilling processes and workforce-related analytics. One industry where AI has the ability to completely change is HR Tech. Here, artificial intelligence will be used to describe machine and/or deep learning algorithms that can automate and subsequently enhance quantitatively the process of matching job offers and job searchers over time. Additionally, it offers a qualitative improvement because algorithms have the potential to produce HRM outcomes that are quicker, more accurate, and more consistent thanks to technological and scientific advancements made in areas like Natural Language Processing (NLP) and the behavioural and brain sciences. Machine learning is already quite effective at determining candidates' talents and motivations and forecasting job fit and performance. Individuals and organizations that design, develop, and implement AI-based HRM solutions must make sure that the cutting-edge solutions they provide are ethical and inclusive in order to avoid discriminatory and unfair outcomes as these solutions grow in popularity and influence. Even if it is still in its infancy compared to more developed industries like healthcare, food and agriculture, transportation, or energy. However, it is still debatable whether HR Tech is actually improving society, which is a need for designating any technology as responsible. HR Tech needs to be moral and inclusive in order to be taken seriously. It suggests that algorithms should not discriminate against people and should offer as many equal opportunities as they can, in addition to producing ethical results that are consequently morally acceptable.

Integration of public policy and self-regulation for responsible artificial intelligence

Social concerns over the alleged "black box" operation of AI-powered items developed for profit gained traction as artificial intelligence permeated throughout society. Some of these concerns are justified if algorithmic findings reveal blatant biases that unfairly affect how people obtain the advantages of AI-assisted solutions. Although difficult to implement, algorithmic openness is essential to boosting consumer confidence. Numerous companies have taken proactive steps to introduce and put into practice the concepts and guidelines for implementing AI. Although there isn't much agreement on how these principles should be expressed or used, they should contain both fundamental epistemic guidelines and ethical standards. It's interesting to note that responsible AI has developed into a separate industry. Companies can now benefit from specific technology solutions, such as Credo AI2, which provides an end-to-end governance platform for managing compliance and evaluating risk for your AI deployments at scale. Companies that provide professional services assist organisations in implementing moral AI norms.

It is important for big tech businesses have made enormous efforts to adopt and, for the most part, execute responsible AI principles since they are always the target of public opinion, media attention, and regulatory scrutiny. Although they are gaining speed, these initiatives are not yet widespread in the start-up ecosystem but they ought to do so as quickly as possible. Due to the "fake AI" problem, where some organisations pretend to be developing AI solutions when they are not, some small businesses try their best to stay under the radar when it comes to responsible AI or evaluation of the truth of their AI solutions. From a business, ethical, and regulatory standpoint, this is not a viable position.

Technology that has been the most well-liked and frequently utilized in human resources management, and more specifically in the recruitment. These techniques are designed to record a person's personality traits, cognitive capacities, and talents in addition to offering predictions about job fit and success or failure in job performance. Public and private organisations still heavily rely on declarative methods in human resources management despite more than forty years of credible scientific literature highlighting their lack of reliability, reproducibility, and predictive power of job fit or performance. This may be because there is nothing better or because it is impossible to implement more rigorous solutions at scale.