Search results

This case is designed to enable students to understand the role of women in artificial intelligence (AI); understand the importance of ethics and diversity in the AI field; discuss the ethical issues of AI; study the implications of unethical AI; examine the dark side of corporate-backed AI research and the difficult relationship between corporate interests and AI ethics research; understand the role played by Gebru in promoting diversity and ethics in AI; and explore how Gebru can attract more women researchers in AI and lead the movement toward inclusive and equitable technology.

The case discusses how Timnit Gebru (She), a prominent AI researcher and former co-lead of the Ethical AI research team at Google, is leading the way in promoting diversity, inclusion and ethics in AI. Gebru, one of the most high-profile black women researchers, is an influential voice in the emerging field of ethical AI, which identifies issues based on bias, fairness, and responsibility. Gebru was fired from Google in December 2020 after the company asked her to retract a research paper she had co-authored about the pitfalls of large language models and embedded racial and gender bias in AI. While Google maintained that Gebru had resigned, she said she had been fired from her job after she had raised issues of discrimination in the workplace and drawn attention to bias in AI. In early December 2021, a year after being ousted from Google, Gebru launched an independent community-driven AI research organization called Distributed Artificial Intelligence Research (DAIR) to develop ethical AI, counter the influence of Big Tech in research and development of AI and increase the presence and inclusion of black researchers in the field of AI. The case discusses Gebru’s journey in creating DAIR, the goals of the organization and some of the challenges she could face along the way. As Gebru seeks to increase diversity in the field of AI and reduce the negative impacts of bias in the training data used in AI models, the challenges before her would be to develop a sustainable revenue model for DAIR, influence AI policies and practices inside Big Tech companies from the outside, inspire and encourage more women to enter the AI field and build a decentralized base of AI expertise.

This case is meant for MBA students.

Teaching Notes are available for educators only.

CCS 11: Strategy

This research examines Indian women entrepreneurs’ endeavours to keep their undertakings above water amid the COVID-19 emergency in 2021–2022. This study centers around female-possessed endeavours in Rajasthan, with a particular spotlight on how artificial intelligence (AI) assists them in getting by. It examines how Indian women entrepreneurs used social media to stay in business during the pandemic and adds to information collection by inspecting women-claimed micro and small enterprises (MSEs) and their use of AI through social media during COVID-19. We administered a questionnaire to a sample of 100 female entrepreneurs who use social media platforms to manage their businesses. The researchers found that the pandemic fundamentally affects women entrepreneurs, especially those who run MSEs, using an anti-tactical approach to deal with survey information from 100 respondents. Women have seen a drop in pay because of lower deals, hindered supply chains, and the inconvenience of paying credit portions. Regardless of how women entrepreneurs are especially delicate to monetary shocks, most need to approach government or private-area help. The significance of virtual entertainment through AI in saving women’s ventures is featured in this review. Web-based entertainment has become famous for helping women sell their businesses, contact new clients, and keep current clients. Women entrepreneurs have reduced their losses as a result of forceful advancements supplemented by appealing offers like limits, various administrations, and advertising. We infer that during an emergency, women entrepreneurs embraced innovative methods to keep their businesses reasonable.

Gender bias in artificial intelligence (AI) should be solved as a priority before AI algorithms become ubiquitous, perpetuating and accentuating the bias. While the problem has been identified as an established research and policy agenda, a cohesive review of existing research specifically addressing gender bias from a socio-technical viewpoint is lacking. Thus, the purpose of this study is to determine the social causes and consequences of, and proposed solutions to, gender bias in AI algorithms.

A comprehensive systematic review followed established protocols to ensure accurate and verifiable identification of suitable articles. The process revealed 177 articles in the socio-technical framework, with 64 articles selected for in-depth analysis.

Most previous research has focused on technical rather than social causes, consequences and solutions to AI bias. From a social perspective, gender bias in AI algorithms can be attributed equally to algorithmic design and training datasets. Social consequences are wide-ranging, with amplification of existing bias the most common at 28%. Social solutions were concentrated on algorithmic design, specifically improving diversity in AI development teams (30%), increasing awareness (23%), human-in-the-loop (23%) and integrating ethics into the design process (21%).

This systematic review is the first of its kind to focus on gender bias in AI algorithms from a social perspective within a socio-technical framework. Identification of key causes and consequences of bias and the breakdown of potential solutions provides direction for future research and policy within the growing field of AI ethics.

The peer review history for this article is available at https://publons.com/publon/10.1108/OIR-08-2021-0452

The purpose of this paper is to present some of the findings (which were reported on more extensively in earlier work) regarding the visibility of gender issues in the literature on selected information and communication technologies (ICTs) with a view to make predictions about potential ethical issues that the application of these ICTs may bring about in the future. This paper is part of the larger research project called ETICA (Ethical Issues of Emerging Information and Communication Technologies), a collaborative project funded by the 7th Framework Programme of the European Union.

On the basis of the analysis of around 100 published sources, which dealt with various aspects of selected ICTs, conclusions have been drawn regarding gender issues and concerns that the applications of these ICTs may cause. The authors' analysis is theoretically informed by critical discourse analysis (CDA) which assumes that texts, both written and spoken, as well as other forms of symbolic representations, are indicative of social practices. Of particular methodological relevance was the survey of methods of text and discourse analysis presented in Titscher et al. and especially the application of keyword search as a way to measure the prominence of each investigated method. This approach to literature surveying proved very useful in selecting analytic material: only those published sources on the selected four ICTs have been included in the survey, for which the analysis of keywords, abstracts and indexes of terms indicated authors' interest in gender issues.

First, ICTs such as affective computing, ambient intelligence, and artificial intelligence, have been found to have the potential of positively affecting gender power relations and thus positively affecting gender balance in the areas of labour market related to ICT across EU countries and worldwide. Second, more research on the relationship between gender and ICT design, application and representation is needed, so as to enhance a better understanding of ethical issues resulting from unequal participation of women and men in all aspects of ICT production and implementation, which in itself is an ethical dilemma with which both the ICT business and legislators have to grapple.

The paper offers insight into the relationship between the level of attention devoted to particular ICTs by ICT researchers, as evidenced in the reviewed literature, and the likelihood of the application of a particular ICT in the future, which is looked at and assessed from a gender perspective.

This study develops a measure of anticipated chilly climate for women and provides initial evidence of its validity.

We draw on three studies. Study 1 consisted of three focus groups to gain deeper insights into the meaning of the concept for prospective female jobseekers and generate scale items. In Study 2, we pre-tested job post vignettes (N = 203), refined the scale items and explored the factor structure (N = 136). Study 3 aimed to determine the convergent and discriminant validity of the new scale (N = 224) by testing its relationships with organisational attractiveness, person-organisation fit perceptions and gendered language.

The results show that the anticipated chilly climate is an important concept with implications for applicants’ career decision-making and career growth in the technology industry, where women tend to be underrepresented. Perceptions of anticipated chilly climate comprise expectations of devaluation, marginalisation and exclusion from the prospective employment. The masculine stereotypes embedded in the language of the job posts signalled a chilly climate for both genders, negatively affecting perceptions of fit and organisational attractiveness.

Most previous studies have focussed on the actual experiences of chilly climates in organisations. We extend this body of literature to anticipatory climates and draw on social identity threat theory and signalling theory to highlight that job applicants make inferences about the climate they expect to find based on job ads. Specifically, they may anticipate a chilly climate based on cues from job ads signalling masculine stereotypes. Whilst the literature has emphasised women’s perceptions of chilly climates within organisations, our results show that both genders anticipate chilly climates with detrimental consequences for both organisations and prospective job applications.

The purpose of this paper is clearly illustrate this convergence and the prescriptive recommendations that such documents entail. There is a significant amount of research into the ethical consequences of artificial intelligence (AI). This is reflected by many outputs across academia, policy and the media. Many of these outputs aim to provide guidance to particular stakeholder groups. It has recently been shown that there is a large degree of convergence in terms of the principles upon which these guidance documents are based. Despite this convergence, it is not always clear how these principles are to be translated into practice.

In this paper, the authors move beyond the high-level ethical principles that are common across the AI ethics guidance literature and provide a description of the normative content that is covered by these principles. The outcome is a comprehensive compilation of normative requirements arising from existing guidance documents. This is not only required for a deeper theoretical understanding of AI ethics discussions but also for the creation of practical and implementable guidance for developers and users of AI.

In this paper, the authors therefore provide a detailed explanation of the normative implications of existing AI ethics guidelines but directed towards developers and organisational users of AI. The authors believe that the paper provides the most comprehensive account of ethical requirements in AI currently available, which is of interest not only to the research and policy communities engaged in the topic but also to the user communities that require guidance when developing or deploying AI systems.

The authors believe that they have managed to compile the most comprehensive document collecting existing guidance which can guide practical action but will hopefully also support the consolidation of the guidelines landscape. The authors’ findings should also be of academic interest and inspire philosophical research on the consistency and justification of the various normative statements that can be found in the literature.

The purpose of this paper is to investigate ethical leadership in the context of the Arab educational system in Israel. It questions the relations of ethical leadership dimensions with decision making as well as background characteristics of the educational leaders.

Arab educational leaders (n=150) from diverse Arab schools responded to valid research tool of 40 items constructed of six subscales: three ethical leadership dimensions (critique, justice and care) and three leadership work aspects (ethical sensitivity, climate and decision making). Averages were calculated for each subscale.

Significant relations were found among ethical leadership dimensions and decision making, the leaders’ school type and their seniority.

This study is based on research in diverse countries, using a common conceptual frame. Its limitation is the sample’s narrow scope.

The study results may inform the developing ethical qualities in educational leadership.

The authors recommend widening the scope of the sample examined to further clarify the concept of ethical leadership and its implications to the practice of educational leadership.

Artificial intelligence (AI) is currently one of the most disruptive technologies and can be applied in many different use cases. However, applying AI in regulated environments is challenging, as it is currently not clear how to achieve and assess the fairness, accountability and transparency (FAT) of AI. Documentation is one promising governance mechanism to ensure that AI is FAT when it is applied in practice. However, due to the nature of AI, documentation standards from software engineering are not suitable to collect the required evidence. Even though FAT AI is called for by lawmakers, academics and practitioners, suitable guidelines on how to document AI are not available. This interview study aims to investigate the requirements for AI documentations.

A total of 16 interviews were conducted with senior employees from companies in the banking and IT industry as well as with consultants. The interviews were then analyzed using an informed-inductive coding approach.

The authors found five requirements for AI documentation, taking the specific nature of AI into account. The interviews show that documenting AI is not a purely technical task, but also requires engineers to present information on how the AI is understandably integrated into the business process.

This paper benefits from the unique insights of senior employees into the documentation of AI.

Historically, it has been common practice for doctors and parents to withhold the diagnosis from their minor intersex patients. This study seeks to integrate intersex youth experiences into the growing body of literature on diagnosis disclosure for intersex patients.

Using gender structure theory as a model, 16 intersex youth were given in-depth surveys regarding their experiences with their intersex identity in individual, interactional, and institutional contexts.

Participants more positively experience intersex than the earlier generations of intersex people. They were not deeply troubled by their diagnosis as doctors have historically feared, and they are open about their diagnosis with their non-intersex peers and teachers. They also find peer support valuable.

Data was collected from a single event and cannot represent all intersex youth. Future research must continue to engage with intersex youth experiences both inside of and beyond activist and support group networks.

These findings are strong exploratory evidence for the importance of diagnosis disclosure for intersex youth. Policies of withholding intersex diagnoses in clinical and familial contexts should be reevaluated in light of the experiences of intersex youth.

Diagnosis disclosure for intersex youth creates the potential for increased medical decision-making participation and increased capacity for activism and community building around intersex issues.

Our results encourage future studies that center the experiences of intersex youth, for we conclude that theorizing the lived experiences of intersex people is incomplete without their perspectives.

This study explores insights from key stakeholders into the skills they believe will be necessary for the future of work as we become more reliant on artificial intelligence (AI) and technology. The study also seeks to understand what human resource policies and educational interventions are needed to support and take advantage of these changes.

This is a qualitative study where a sample of highly experienced representatives from a range of small to large Irish organisations, both public and private, provide insights into this important topic.

Findings indicate participants see a continued need for soft and hard skills as we evolve towards a more technologised workplace, with a need for employees to adopt a lifelong learning philosophy. As the knowledge economy in Ireland is well established, experts do not expect mass displacement to occur but differ with respect to the predicted rate of change. Novel HR interventions such as hiring for potential, pooling talent and establishing postgraduate supply contracts are seen as key. Current state interventions were mostly viewed positively but revamping of curricula is needed as well as stronger partnerships with tertiary institutions.

The interpretivist nature of the study limits the generalisability of the findings as they are based on a relatively small sample from one country. Also despite the significant expertise of the sample, it is not possible to predict whether their forecasts will manifest.

This research highlights the need for Irish SMEs to embrace the impacts of automation and AI as many are seen to be slow in reacting to changes in technology. The study also reveals cutting edge talent management interventions for employers to adopt that will insulate them from the challenges technological change presents to recruitment and employee development.

The findings from this paper culminate in the development of a conceptual framework, which encapsulates the responsibilities of all parties so that future skills needs will be met. This highlights the interplay between employers, individuals/employees, the Irish Government and educational institutions, demonstrating how they are interdependent on one another as we move towards a more technologised future.