An Ethical Framework for a Good AI Society: Opportunities, Risks, Principles, and Recommendations

Floridi, Luciano; Cowls, Josh; Beltrametti, Monica; Chatila, Raja; Chazerand, Patrice; Dignum, Virginia; Luetge, Christoph; Madelin, Robert; Pagallo, Ugo; Rossi, Francesca; Schäfer, Burkhard; Valcke, Peggy; Vayena, Effy

doi:10.1007/978-3-030-81907-1_3

Cited by 61 publications

(44 citation statements)

References 3 publications

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“…As algorithms drive critical decisions about gig work assignment and design, human workers deserve to be treated ethically rather than being digitized on the platform (Connelly et al, 2021). Although the ethical design of algorithms has been widely discussed in different fields, including sociology, computer science (Kearns & Roth, 2019), and philosophy (Floridi et al, 2021), our findings show that the design principles were not often identified specifically for gig economy platforms. Considering the growing focus on ethical practices, further research in this area is vital for the long-term success of platform companies and the gig workforce.…”

Section: Understudied Socio-technical Issues In the Gig Economymentioning

confidence: 82%

Socio‐technical issues in the platform‐mediated gig economy: A systematic literature review: An Annual Review of Information Science and Technology (ARIST) paper

Dedema,

Rosenbaum

2024

Asso for Info Science & Tech

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The gig economy and gig work have grown quickly in recent years and have drawn much attention from researchers in different fields. Because the platform mediated gig economy is a relatively new phenomenon, studies have produced a range of interesting findings; of interest here are the socio‐technical issues that this work has surfaced. This systematic literature review (SLR) provides a snapshot of a range of socio‐technical issues raised in the last 12 years of literature focused on the platform mediated gig economy. Based on a sample of 515 papers gathered from nine databases in multiple disciplines, 132 were coded that specifically studied the gig economy, gig work, and gig workers. Three main socio‐technical themes were identified: (1) the digital workplace, which includes information infrastructure and digital labor that are related to the nature of gig work and the user agency; (2) algorithmic management, which includes platform governance, performance management, information asymmetry, power asymmetry, and system manipulation, relying on a diverse set of technological tools including algorithms and big data analytics; (3) ethical design, as a relevant value set that gig workers expect from the platform, which includes trust, fairness, equality, privacy, and transparency. A social informatics perspective is used to rethink the relationship between gig workers and platforms, extract the socio‐technical issues noted in prior research, and discuss the underexplored aspects of the platform mediated gig economy. The results draw attention to understudied yet critically important socio‐technical issues in the gig economy that suggest short‐ and long‐term opportunities for future research directions.

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Section: Understudied Socio-technical Issues In the Gig Economymentioning

confidence: 82%

Socio‐technical issues in the platform‐mediated gig economy: A systematic literature review: An Annual Review of Information Science and Technology (ARIST) paper

Dedema,

Rosenbaum

2024

Asso for Info Science & Tech

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“…In addition, businesses might establish ethical rules highlighting the need for openness and responsibility in creating and implementing AI-powered marketing initiatives. This may involve the creation of clear accountability lines for the development and deployment of AI algorithms, as well as ways for customers to file complaints or express concerns (Floridi et al , 2021). Companies may aid in identifying and addressing unintended repercussions of AI-powered marketing initiatives by providing explicit responsibility and transparency.…”

Section: Resultsmentioning

confidence: 99%

“…The difficulty of attributing blame when anything goes wrong is one of the key problems. Complex and difficult-to-understand AI algorithms make it tough to determine who is accountable for any resulting problems (Floridi et al , 2021). Furthermore, using AI in marketing might generate new ethical concerns that current laws or regulations may not address.…”

Section: Resultsmentioning

confidence: 99%

Ethical and legal challenges of AI in marketing: an exploration of solutions

Kumar,

Suthar

2024

JICES

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Purpose Artificial intelligence (AI) has sparked interest in various areas, including marketing. However, this exhilaration is being tempered by growing concerns about the moral and legal implications of using AI in marketing. Although previous research has revealed various ethical and legal issues, such as algorithmic discrimination and data privacy, there are no definitive answers. This paper aims to fill this gap by investigating AI’s ethical and legal concerns in marketing and suggesting feasible solutions. Design/methodology/approach The paper synthesises information from academic articles, industry reports, case studies and legal documents through a thematic literature review. A qualitative analysis approach categorises and interprets ethical and legal challenges and proposes potential solutions. Findings The findings of this paper raise concerns about ethical and legal challenges related to AI in the marketing area. Ethical concerns related to discrimination, bias, manipulation, job displacement, absence of social interaction, cybersecurity, unintended consequences, environmental impact, privacy and legal issues such as consumer security, responsibility, liability, brand protection, competition law, agreements, data protection, consumer protection and intellectual property rights are discussed in the paper, and their potential solutions are discussed. Research limitations/implications Notwithstanding the interesting insights gathered from this investigation of the ethical and legal consequences of AI in marketing, it is important to recognise the limits of this research. Initially, the focus of this study is confined to a review of the most important ethical and legal issues pertaining to AI in marketing. Additional possible repercussions, such as those associated with intellectual property, contracts and licencing, should be investigated more deeply in future studies. Despite the fact that this study gives various answers and best practices for tackling the stated ethical and legal concerns, the viability and efficacy of these solutions may differ depending on the context and industry. Thus, more research and case studies are required to evaluate the applicability and efficacy of these solutions in other circumstances. This research is mostly based on a literature review and may not represent the experiences or opinions of all stakeholders engaged in AI-powered marketing. Further study might involve interviews or surveys with marketing professionals, customers and other key stakeholders to offer a full knowledge of the practical difficulties and solutions. Because of the rapid speed of technical progress, AI’s ethical and regulatory ramifications in marketing are continually increasing. Consequently, this work should be a springboard for more research and continuing conversations on this subject. Practical implications This study’s findings have several practical implications for marketing professionals. Emphasising openness and explainability: Marketing professionals should prioritise transparency in their use of AI, ensuring that customers are fully informed about data collection and utilisation for targeted advertising. By promoting openness and explainability, marketers can foster customer trust and avoid the negative consequences of a lack of transparency. Establishing ethical guidelines: Marketing professionals need to develop ethical rules for the creation and implementation of AI-powered marketing strategies. Adhering to ethical principles ensures compliance with legal norms and aligns with the organisation’s values and ideals. Investing in bias detection tools and privacy-enhancing technology: To mitigate risks associated with AI in marketing, marketers should allocate resources to develop and implement bias detection tools and privacy-enhancing technology. These tools can identify and address biases in AI algorithms, safeguard consumer privacy and extract valuable insights from consumer data. Social implications This study’s social implications emphasise the need for a comprehensive approach to address the ethical and legal challenges of AI in marketing. This includes adopting a responsible innovation framework, promoting ethical leadership, using ethical decision-making frameworks and conducting multidisciplinary research. By incorporating these approaches, marketers can navigate the complexities of AI in marketing responsibly, foster an ethical organisational culture, make informed ethical decisions and develop effective solutions. Such practices promote public trust, ensure equitable distribution of benefits and risk, and mitigate potential negative social consequences associated with AI in marketing. Originality/value To the best of the authors’ knowledge, this paper is among the first to explore potential solutions comprehensively. This paper provides a nuanced understanding of the challenges by using a multidisciplinary framework and synthesising various sources. It contributes valuable insights for academia and industry.

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“…In these applications, the autonomous agents are often required to perform normative tasks that raise social, legal, ethical, empathetic, and cultural (SLEEC) concerns [2]. There is widespread agreement that these concerns must be considered throughout the development of the agents [3,4], and numerous guidelines propose high-level principles that reflect them [5,6,7,8]. However, to follow these guidelines, the engineers developing the control software of autonomous agents need methods and tools that support formalisation, validation and verification of SLEEC requirements.…”

Section: Introductionmentioning

confidence: 99%

Specification and Validation of Normative Rules for Autonomous Agents

Yaman

Burholt

Jones

et al. 2023

Lecture Notes in Computer Science

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A growing range of applications use autonomous agents such as AI and robotic systems to perform tasks deemed dangerous, tedious or costly for humans. To truly succeed with these tasks, the autonomous agents must perform them without violating the social, legal, ethical, empathetic, and cultural (SLEEC) norms of their users and operators. We introduce SLEECVAL, a tool for specification and validation of rules that reflect these SLEEC norms. Our tool supports the specification of SLEEC rules in a DSL [1] we co-defined with the help of ethicists, lawyers and stakeholders from health and social care, and uses the CSP refinement checker FDR4 to identify redundant and conflicting rules in a SLEEC specification. We illustrate the use of SLEECVAL for two case studies: an assistive dressing robot, and a firefighting drone.

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An Ethical Framework for a Good AI Society: Opportunities, Risks, Principles, and Recommendations

Cited by 61 publications

References 3 publications

Socio‐technical issues in the platform‐mediated gig economy: A systematic literature review: An Annual Review of Information Science and Technology (ARIST) paper

Socio‐technical issues in the platform‐mediated gig economy: A systematic literature review: An Annual Review of Information Science and Technology (ARIST) paper

Ethical and legal challenges of AI in marketing: an exploration of solutions

Specification and Validation of Normative Rules for Autonomous Agents

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