Karen Elliott | University of Birmingham (original) (raw)
Papers by Karen Elliott
arXiv (Cornell University), Apr 21, 2022
Academy of Management Proceedings, 2015
Based on 148 interviews with European police officers, we explore the role of negative external s... more Based on 148 interviews with European police officers, we explore the role of negative external stakeholder feedback in shaping professional identities. We find that attributional processes act as a buffer against external critique, allowing individuals to maintain positive perceptions of their profession and avoid disidentification. We discuss the implications of these findings for multi-level outcomes, including stakeholder relations and organizational learning.
ArXiv, 2021
Financial inclusion depends on providing adjusted services for citizens with disclosed vulnerabil... more Financial inclusion depends on providing adjusted services for citizens with disclosed vulnerabilities. At the same time, the financial industry needs to adhere to a strict regulatory framework, which is often in conflict with the desire for inclusive, adaptive, privacy-preserving services. In this paper we study how this tension impacts the deployment of privacy-sensitive technologies aimed at financial inclusion. We conduct a qualitative study with banking experts to understand their perspective on service development for financial inclusion. We build and demonstrate a prototype solution based on open source decentralized identifiers and verifiable credentials software and report on feedback from the banking experts on this system. The technology is promising thanks to its selective disclosure of vulnerabilities to the full control of the individual. This support GDPR requirement, but at the same time, there is a clear tension between introducing these technologies and fulfilling ...
Society, 2021
In the digital era, we witness the increasing use of artificial intelligence (AI) to solve proble... more In the digital era, we witness the increasing use of artificial intelligence (AI) to solve problems, while improving productivity and efficiency. Yet, inevitably costs are involved with delegating power to algorithmically based systems, some of whose workings are opaque and unobservable and thus termed the “black box”. Central to understanding the “black box” is to acknowledge that the algorithm is not mendaciously undertaking this action; it is simply using the recombination afforded to scaled computable machine learning algorithms. But an algorithm with arbitrary precision can easily reconstruct those characteristics and make life-changing decisions, particularly in financial services (credit scoring, risk assessment, etc.), and it could be difficult to reconstruct, if this was done in a fair manner reflecting the values of society. If we permit AI to make life-changing decisions, what are the opportunity costs, data trade-offs, and implications for social, economic, technical, le...
ArXiv, 2020
Concerns about the societal impact of AI-based services and systems has encouraged governments an... more Concerns about the societal impact of AI-based services and systems has encouraged governments and other organisations around the world to propose AI policy frameworks to address fairness, accountability, transparency and related topics. To achieve the objectives of these frameworks, the data and software engineers who build machine-learning systems require knowledge about a variety of relevant supporting tools and techniques. In this paper we provide an overview of technologies that support building trustworthy machine learning systems, i.e., systems whose properties justify that people place trust in them. We argue that four categories of system properties are instrumental in achieving the policy objectives, namely fairness, explainability, auditability and safety & security (FEAS). We discuss how these properties need to be considered across all stages of the machine learning life cycle, from data collection through run-time model inference. As a consequence, we survey in this pa...
Vulnerable individuals have a limited ability to make reasonable financial decisions and choices ... more Vulnerable individuals have a limited ability to make reasonable financial decisions and choices and, thus, the level of care that is appropriate to be provided to them by financial institutions may be different from that required for other consumers. Therefore, identifying vulnerability is of central importance for the design and effective provision of financial services and products. However, validating the information that customers share and respecting their privacy are both particularly important in finance and this poses a challenge for identifying and caring for vulnerable populations. This position paper examines the potential of the combination of two emerging technologies, Decentralized Identifiers (DIDs) and Verifiable Credentials (VCs), for the identification of vulnerable consumers in finance in an efficient and privacy-preserving manner.
Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency, 2020
To design and develop AI-based systems that users and the larger public can justifiably trust, on... more To design and develop AI-based systems that users and the larger public can justifiably trust, one needs to understand how machine learning technologies impact trust. To guide the design and implementation of trusted AI-based systems, this paper provides a systematic approach to relate considerations about trust from the social sciences to trustworthiness technologies proposed for AI-based services and products. We start from the ABI+ (Ability, Benevolence, Integrity, Predictability) framework augmented with a recently proposed mapping of ABI+ on qualities of technologies that support trust. We consider four categories of trustworthiness technologies for machine learning, namely these for Fairness, Explainability, Auditability and Safety (FEAS) and discuss if and how these support the required qualities. Moreover, trust can be impacted throughout the life cycle of AI-based systems, and we therefore introduce the concept of Chain of Trust to discuss trustworthiness technologies in all stages of the life cycle. In so doing we establish the ways in which machine learning technologies support trusted AI-based systems. Finally, FEAS has obvious relations with known frameworks and therefore we relate FEAS to a variety of international 'principled AI' policy and technology frameworks that have emerged in recent years. CCS CONCEPTS • Applied computing → Sociology; • Social and professional topics → Computing / technology policy; • Security and privacy → Human and societal aspects of security and privacy; • Computing methodologies → Artificial intelligence; Machine learning.
Technology in Society, 2021
While the field of data ethics is increasingly engaging with the complex socio-technical nature o... more While the field of data ethics is increasingly engaging with the complex socio-technical nature of data practices and their impacts, in the private sector, data ethics continues to be pursued largely through limited instrumental measures. This paper addresses the following research question: How can socially-minded data-intensive innovation be pursued in the private sector? It reports the findings of a series of five focus groups to explore the role of public deliberation in informing ethical data practices in banking. The findings indicate that deliberative forms of public engagement present valuable opportunities to incorporate diverse views and perspectives and to enable critical reflection on organisational practices and the trajectory of innovation. We conclude that public engagement is vital to ensure that private sector organisations move beyond "ethics-washing" or tokenistic efforts at Corporate Digital Responsibility (CDR) to meaningfully address public concerns and reflect public values in all innovation processes.
Computer Security, 2020
While there is substantial interest in ethical practice relating to Artificial Intelligence (AI),... more While there is substantial interest in ethical practice relating to Artificial Intelligence (AI), to date there has been limited consideration of what this means in the banking sector. This study aimed to address this gap in the literature through a qualitative study of public attitudes and perceptions of current and potential future uses of AI in banking. A series of focus groups were conducted with with diverse members of the public. Focus group participants were largely positive about the role of AI in speeding up financial processes and increasing efficiency. Yet, they also expressed a number of concerns around potential negative impacts on society and consistently emphasized the importance of human judgement or oversight. The findings suggest a potential cognitive dissonance where people use new services due to perceived convenience or immediate benefits, while disliking or distrusting those services or holding concerns about their impacts on society. The findings illustrate that participants' concerns did not typically relate to private or individual interests but more often to wider ethical and social concerns. The focus groups demonstrated the value of qualitative, deliberative methods to explore the nuances of public responses and highlighted the importance of taking account of conditions for public acceptability-rather than just customer uptake-in order to develop ethical practice and establish a social licence for uses of AI in banking.
Cyber-security tends to be viewed as a highly dynamic continually evolving technology race betwee... more Cyber-security tends to be viewed as a highly dynamic continually evolving technology race between attacker and defender. However, economic theory suggests that in many cases doing ‘nothing’ is the optimal strategy when substantial fixed adjustments costs are present. Indeed, anecdotal experience off chief information security officers by the authors indicates that uncertain costs that might be incurred by rapid adoption of security updates does induce substantial delay, so the industry does appear to understand this aspect of economics quite well. From a policy perspective the inherently discontinuous adjustment path taken by firms can cause difficulties in determining a) the most effective public policy remit and b) assessing the effectiveness of any enacted policies ex-post. This article provides a short summary of the key ideas of the pressing policy issues on the cyber security agenda.
International Journal of Operations & Production Management
Purpose Developing and implementing strategies to maximize profitability is a fundamental challen... more Purpose Developing and implementing strategies to maximize profitability is a fundamental challenge facing manufacturers. The complexity of orchestrating resources in practice has been overlooked in the operations field and it is now necessary to go beyond the direct effects of individual resources and uncover different resource configurations that maximize profitability. The paper aims to discuss these issues. Design/methodology/approach Drawing on a sample of US manufacturing firms, multiple regression analysis (MRA) and fuzzy set qualitative comparative analysis (fsQCA) are performed to examine the effects of resource orchestration on firm profitability over time. By comparing the findings between analyses, the study represents a move away from examining the net effects of resource levers on performance alone. Findings The findings characterize the resource conditions for manufacturers’ high performance, and also for absence of high performance. Pension and retirement expense is ...
European Management Review
Journal of Organizational Change Management
In the tradition of organizational ecology, Hannan, Pólos and Carroll (2003a, 2003b, 2007) sugges... more In the tradition of organizational ecology, Hannan, Pólos and Carroll (2003a, 2003b, 2007) suggested a cognitive turn in the theory of organizational change, emphasizing the role of subtle processes of appeal and engagement in determining the likelihood of organizational change success, and the subsequent impact on the organization's hazard of failure, conditional on important aspects of the organization's texture. In the current paper, we suggest a series of measures to proxy for the theory's key theoretical constructs, and run psychometric analyses with data from two pilot studies. We collected tailor-made survey data from police forces in Belgium and the UK, and provide evidence for a cognitive organization theory of organizational change.
SSRN Electronic Journal, 2000
We present a new conceptual model of disruptive innovation and apply it to the emerging financial... more We present a new conceptual model of disruptive innovation and apply it to the emerging financial technology of distributed ledgers and smart contracts. Our analysis illustrates the new features of this technology and why there is an argument that, in several respects, the combination of distributed ledger technology and cryptographically enabled contracts changes the economic framework within which individuals, firms and policy makers reside. This foundational level of disruption appears to have several new features, more notably a fundamental change in the game played by economic actors: the ability to self-deregulate. The paper clarifies these complex interactions and illustrates the main points using a recent case study from the Distributed Autonomous Organizations of the Ethereum project as well from a mathematical standpoint. Automation and distribution with powerful computing languages boost the speed of seizing opportunities as well as of tripping into (in-eliminable) severe risks.
SSRN Electronic Journal, 2000
IEEE Security & Privacy, 2016
Cyber-security tends to be viewed as a highly dynamic continually evolving technology race betwee... more Cyber-security tends to be viewed as a highly dynamic continually evolving technology race between attacker and defender. However, economic theory suggests that in many cases doing 'nothing' is the optimal strategy when substantial fixed adjustments costs are present. Indeed, anecdotal experience off chief information security officers by the authors indicates that uncertain costs that might be incurred by rapid adoption of security updates does induce substantial delay, so the industry does appear to understand this aspect of economics quite well. From a policy perspective the inherently discontinuous adjustment path taken by firms can cause difficulties in determining a) the most effective public policy remit and b) assessing the effectiveness of any enacted policies ex-post. This article provides a short summary of the key ideas of the pressing policy issues on the cyber security agenda.
Big Data & Society
Current attention directed at ethical dimensions of data and Artificial Intelligence have led to ... more Current attention directed at ethical dimensions of data and Artificial Intelligence have led to increasing recognition of the need to secure and maintain public support for uses (and reuses) of people's data. This is essential to establish a "Social Licence" for current and future practices. The notion of a "Social Licence" recognises that there can be meaningful differences between what is legally permissible and what is socially acceptable. Establishing a Social Licence entails public engagement to build relationships of trust and ensure that practices align with public values. While the concept of the Social Licence is well-established in other sectors-notably in relation to extractive industries-it has only very recently begun to be discussed in relation to digital innovation and data-intensive industries. This article therefore draws on existing literature relating to the Social Licence in extractive industries to explore the potential approaches needed to establish a Social Licence for emerging data-intensive industries. Additionally, it draws on well-established literature relating to trust (from psychology and organisational science) to examine the relevance of trust, and trustworthiness, for emerging practices in data-intensive industries. In doing so the article considers the extent to which pursuing a Social Licence might complement regulation and inform codes of practice to place ethical and social considerations at the heart of industry practice. We focus on one key industry: Financial Technology. We demonstrate the importance of combining technical and social approaches to address ethical challenges in data-intensive innovation (particularly relating to Artificial Intelligence) and to establish relationships of trust to underpin a Social Licence for Financial Technology. Such approaches are needed across all areas and industries of data-intensive innovation to complement regulation and inform the development of ethical codes of practice. This is important to underpin culture change and to move beyond rhetorical commitments to develop best practice putting ethics at the heart of innovation.
arXiv (Cornell University), Apr 21, 2022
Academy of Management Proceedings, 2015
Based on 148 interviews with European police officers, we explore the role of negative external s... more Based on 148 interviews with European police officers, we explore the role of negative external stakeholder feedback in shaping professional identities. We find that attributional processes act as a buffer against external critique, allowing individuals to maintain positive perceptions of their profession and avoid disidentification. We discuss the implications of these findings for multi-level outcomes, including stakeholder relations and organizational learning.
ArXiv, 2021
Financial inclusion depends on providing adjusted services for citizens with disclosed vulnerabil... more Financial inclusion depends on providing adjusted services for citizens with disclosed vulnerabilities. At the same time, the financial industry needs to adhere to a strict regulatory framework, which is often in conflict with the desire for inclusive, adaptive, privacy-preserving services. In this paper we study how this tension impacts the deployment of privacy-sensitive technologies aimed at financial inclusion. We conduct a qualitative study with banking experts to understand their perspective on service development for financial inclusion. We build and demonstrate a prototype solution based on open source decentralized identifiers and verifiable credentials software and report on feedback from the banking experts on this system. The technology is promising thanks to its selective disclosure of vulnerabilities to the full control of the individual. This support GDPR requirement, but at the same time, there is a clear tension between introducing these technologies and fulfilling ...
Society, 2021
In the digital era, we witness the increasing use of artificial intelligence (AI) to solve proble... more In the digital era, we witness the increasing use of artificial intelligence (AI) to solve problems, while improving productivity and efficiency. Yet, inevitably costs are involved with delegating power to algorithmically based systems, some of whose workings are opaque and unobservable and thus termed the “black box”. Central to understanding the “black box” is to acknowledge that the algorithm is not mendaciously undertaking this action; it is simply using the recombination afforded to scaled computable machine learning algorithms. But an algorithm with arbitrary precision can easily reconstruct those characteristics and make life-changing decisions, particularly in financial services (credit scoring, risk assessment, etc.), and it could be difficult to reconstruct, if this was done in a fair manner reflecting the values of society. If we permit AI to make life-changing decisions, what are the opportunity costs, data trade-offs, and implications for social, economic, technical, le...
ArXiv, 2020
Concerns about the societal impact of AI-based services and systems has encouraged governments an... more Concerns about the societal impact of AI-based services and systems has encouraged governments and other organisations around the world to propose AI policy frameworks to address fairness, accountability, transparency and related topics. To achieve the objectives of these frameworks, the data and software engineers who build machine-learning systems require knowledge about a variety of relevant supporting tools and techniques. In this paper we provide an overview of technologies that support building trustworthy machine learning systems, i.e., systems whose properties justify that people place trust in them. We argue that four categories of system properties are instrumental in achieving the policy objectives, namely fairness, explainability, auditability and safety & security (FEAS). We discuss how these properties need to be considered across all stages of the machine learning life cycle, from data collection through run-time model inference. As a consequence, we survey in this pa...
Vulnerable individuals have a limited ability to make reasonable financial decisions and choices ... more Vulnerable individuals have a limited ability to make reasonable financial decisions and choices and, thus, the level of care that is appropriate to be provided to them by financial institutions may be different from that required for other consumers. Therefore, identifying vulnerability is of central importance for the design and effective provision of financial services and products. However, validating the information that customers share and respecting their privacy are both particularly important in finance and this poses a challenge for identifying and caring for vulnerable populations. This position paper examines the potential of the combination of two emerging technologies, Decentralized Identifiers (DIDs) and Verifiable Credentials (VCs), for the identification of vulnerable consumers in finance in an efficient and privacy-preserving manner.
Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency, 2020
To design and develop AI-based systems that users and the larger public can justifiably trust, on... more To design and develop AI-based systems that users and the larger public can justifiably trust, one needs to understand how machine learning technologies impact trust. To guide the design and implementation of trusted AI-based systems, this paper provides a systematic approach to relate considerations about trust from the social sciences to trustworthiness technologies proposed for AI-based services and products. We start from the ABI+ (Ability, Benevolence, Integrity, Predictability) framework augmented with a recently proposed mapping of ABI+ on qualities of technologies that support trust. We consider four categories of trustworthiness technologies for machine learning, namely these for Fairness, Explainability, Auditability and Safety (FEAS) and discuss if and how these support the required qualities. Moreover, trust can be impacted throughout the life cycle of AI-based systems, and we therefore introduce the concept of Chain of Trust to discuss trustworthiness technologies in all stages of the life cycle. In so doing we establish the ways in which machine learning technologies support trusted AI-based systems. Finally, FEAS has obvious relations with known frameworks and therefore we relate FEAS to a variety of international 'principled AI' policy and technology frameworks that have emerged in recent years. CCS CONCEPTS • Applied computing → Sociology; • Social and professional topics → Computing / technology policy; • Security and privacy → Human and societal aspects of security and privacy; • Computing methodologies → Artificial intelligence; Machine learning.
Technology in Society, 2021
While the field of data ethics is increasingly engaging with the complex socio-technical nature o... more While the field of data ethics is increasingly engaging with the complex socio-technical nature of data practices and their impacts, in the private sector, data ethics continues to be pursued largely through limited instrumental measures. This paper addresses the following research question: How can socially-minded data-intensive innovation be pursued in the private sector? It reports the findings of a series of five focus groups to explore the role of public deliberation in informing ethical data practices in banking. The findings indicate that deliberative forms of public engagement present valuable opportunities to incorporate diverse views and perspectives and to enable critical reflection on organisational practices and the trajectory of innovation. We conclude that public engagement is vital to ensure that private sector organisations move beyond "ethics-washing" or tokenistic efforts at Corporate Digital Responsibility (CDR) to meaningfully address public concerns and reflect public values in all innovation processes.
Computer Security, 2020
While there is substantial interest in ethical practice relating to Artificial Intelligence (AI),... more While there is substantial interest in ethical practice relating to Artificial Intelligence (AI), to date there has been limited consideration of what this means in the banking sector. This study aimed to address this gap in the literature through a qualitative study of public attitudes and perceptions of current and potential future uses of AI in banking. A series of focus groups were conducted with with diverse members of the public. Focus group participants were largely positive about the role of AI in speeding up financial processes and increasing efficiency. Yet, they also expressed a number of concerns around potential negative impacts on society and consistently emphasized the importance of human judgement or oversight. The findings suggest a potential cognitive dissonance where people use new services due to perceived convenience or immediate benefits, while disliking or distrusting those services or holding concerns about their impacts on society. The findings illustrate that participants' concerns did not typically relate to private or individual interests but more often to wider ethical and social concerns. The focus groups demonstrated the value of qualitative, deliberative methods to explore the nuances of public responses and highlighted the importance of taking account of conditions for public acceptability-rather than just customer uptake-in order to develop ethical practice and establish a social licence for uses of AI in banking.
Cyber-security tends to be viewed as a highly dynamic continually evolving technology race betwee... more Cyber-security tends to be viewed as a highly dynamic continually evolving technology race between attacker and defender. However, economic theory suggests that in many cases doing ‘nothing’ is the optimal strategy when substantial fixed adjustments costs are present. Indeed, anecdotal experience off chief information security officers by the authors indicates that uncertain costs that might be incurred by rapid adoption of security updates does induce substantial delay, so the industry does appear to understand this aspect of economics quite well. From a policy perspective the inherently discontinuous adjustment path taken by firms can cause difficulties in determining a) the most effective public policy remit and b) assessing the effectiveness of any enacted policies ex-post. This article provides a short summary of the key ideas of the pressing policy issues on the cyber security agenda.
International Journal of Operations & Production Management
Purpose Developing and implementing strategies to maximize profitability is a fundamental challen... more Purpose Developing and implementing strategies to maximize profitability is a fundamental challenge facing manufacturers. The complexity of orchestrating resources in practice has been overlooked in the operations field and it is now necessary to go beyond the direct effects of individual resources and uncover different resource configurations that maximize profitability. The paper aims to discuss these issues. Design/methodology/approach Drawing on a sample of US manufacturing firms, multiple regression analysis (MRA) and fuzzy set qualitative comparative analysis (fsQCA) are performed to examine the effects of resource orchestration on firm profitability over time. By comparing the findings between analyses, the study represents a move away from examining the net effects of resource levers on performance alone. Findings The findings characterize the resource conditions for manufacturers’ high performance, and also for absence of high performance. Pension and retirement expense is ...
European Management Review
Journal of Organizational Change Management
In the tradition of organizational ecology, Hannan, Pólos and Carroll (2003a, 2003b, 2007) sugges... more In the tradition of organizational ecology, Hannan, Pólos and Carroll (2003a, 2003b, 2007) suggested a cognitive turn in the theory of organizational change, emphasizing the role of subtle processes of appeal and engagement in determining the likelihood of organizational change success, and the subsequent impact on the organization's hazard of failure, conditional on important aspects of the organization's texture. In the current paper, we suggest a series of measures to proxy for the theory's key theoretical constructs, and run psychometric analyses with data from two pilot studies. We collected tailor-made survey data from police forces in Belgium and the UK, and provide evidence for a cognitive organization theory of organizational change.
SSRN Electronic Journal, 2000
We present a new conceptual model of disruptive innovation and apply it to the emerging financial... more We present a new conceptual model of disruptive innovation and apply it to the emerging financial technology of distributed ledgers and smart contracts. Our analysis illustrates the new features of this technology and why there is an argument that, in several respects, the combination of distributed ledger technology and cryptographically enabled contracts changes the economic framework within which individuals, firms and policy makers reside. This foundational level of disruption appears to have several new features, more notably a fundamental change in the game played by economic actors: the ability to self-deregulate. The paper clarifies these complex interactions and illustrates the main points using a recent case study from the Distributed Autonomous Organizations of the Ethereum project as well from a mathematical standpoint. Automation and distribution with powerful computing languages boost the speed of seizing opportunities as well as of tripping into (in-eliminable) severe risks.
SSRN Electronic Journal, 2000
IEEE Security & Privacy, 2016
Cyber-security tends to be viewed as a highly dynamic continually evolving technology race betwee... more Cyber-security tends to be viewed as a highly dynamic continually evolving technology race between attacker and defender. However, economic theory suggests that in many cases doing 'nothing' is the optimal strategy when substantial fixed adjustments costs are present. Indeed, anecdotal experience off chief information security officers by the authors indicates that uncertain costs that might be incurred by rapid adoption of security updates does induce substantial delay, so the industry does appear to understand this aspect of economics quite well. From a policy perspective the inherently discontinuous adjustment path taken by firms can cause difficulties in determining a) the most effective public policy remit and b) assessing the effectiveness of any enacted policies ex-post. This article provides a short summary of the key ideas of the pressing policy issues on the cyber security agenda.
Big Data & Society
Current attention directed at ethical dimensions of data and Artificial Intelligence have led to ... more Current attention directed at ethical dimensions of data and Artificial Intelligence have led to increasing recognition of the need to secure and maintain public support for uses (and reuses) of people's data. This is essential to establish a "Social Licence" for current and future practices. The notion of a "Social Licence" recognises that there can be meaningful differences between what is legally permissible and what is socially acceptable. Establishing a Social Licence entails public engagement to build relationships of trust and ensure that practices align with public values. While the concept of the Social Licence is well-established in other sectors-notably in relation to extractive industries-it has only very recently begun to be discussed in relation to digital innovation and data-intensive industries. This article therefore draws on existing literature relating to the Social Licence in extractive industries to explore the potential approaches needed to establish a Social Licence for emerging data-intensive industries. Additionally, it draws on well-established literature relating to trust (from psychology and organisational science) to examine the relevance of trust, and trustworthiness, for emerging practices in data-intensive industries. In doing so the article considers the extent to which pursuing a Social Licence might complement regulation and inform codes of practice to place ethical and social considerations at the heart of industry practice. We focus on one key industry: Financial Technology. We demonstrate the importance of combining technical and social approaches to address ethical challenges in data-intensive innovation (particularly relating to Artificial Intelligence) and to establish relationships of trust to underpin a Social Licence for Financial Technology. Such approaches are needed across all areas and industries of data-intensive innovation to complement regulation and inform the development of ethical codes of practice. This is important to underpin culture change and to move beyond rhetorical commitments to develop best practice putting ethics at the heart of innovation.