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Harsha Perera

Publications and source records attributed to Harsha Perera.

14 recordsLinked to original sources

Responsible AI Question Bank: A Comprehensive Tool for AI Risk Assessment

The rapid growth of Artificial Intelligence (AI) has underscored the urgent need for responsible AI practices. Despite increasing interest, a comprehensive AI risk assessment toolkit remains lacking. This study introduces our Responsible AI (RAI) Question Bank, a comprehensive framework and tool designed to support diverse AI initiatives. By integrating AI ethics principles such as fairness, transparency, and accountability into a structured question format, the RAI Question Bank aids in identifying potential risks, aligning with emerging regulations like the EU AI Act, and enhancing overall AI governance. A key benefit of the RAI Question Bank is its systematic approach to linking lower-level risk questions to higher-level ones and related themes, preventing siloed assessments and ensuring a cohesive evaluation process. Case studies illustrate the practical application of the RAI Question Bank in assessing AI projects, from evaluating risk factors to informing decision-making processes. The study also demonstrates how the RAI Question Bank can be used to ensure compliance with standards, mitigate risks, and promote the development of trustworthy AI systems. This work advances RAI by providing organizations with a valuable tool to navigate the complexities of ethical AI development and deployment while ensuring comprehensive risk management.

cs.CY

Achieving Responsible AI through ESG: Insights and Recommendations from Industry Engagement

As Artificial Intelligence (AI) becomes integral to business operations, integrating Responsible AI (RAI) within Environmental, Social, and Governance (ESG) frameworks is essential for ethical and sustainable AI deployment. This study examines how leading companies align RAI with their ESG goals. Through interviews with 28 industry leaders, we identified a strong link between RAI and ESG practices. However, a significant gap exists between internal RAI policies and public disclosures, highlighting the need for greater board-level expertise, robust governance, and employee engagement. We provide key recommendations to strengthen RAI strategies, focusing on transparency, cross-functional collaboration, and seamless integration into existing ESG frameworks.

cs.CY

Integrating ESG and AI: A Comprehensive Responsible AI Assessment Framework

Artificial Intelligence (AI) is a widely developed and adopted technology across entire industry sectors. Integrating environmental, social, and governance (ESG) considerations with AI investments is crucial for ensuring ethical and sustainable technological advancement. Particularly from an investor perspective, this integration not only mitigates risks but also enhances long-term value creation by aligning AI initiatives with broader societal goals. Yet, this area has been less explored in both academia and industry. To bridge the gap, we introduce a novel ESG-AI framework, which is developed based on insights from engagements with 28 companies and comprises three key components. The framework provides a structured approach to this integration, developed in collaboration with industry practitioners. The ESG-AI framework provides an overview of the environmental and social impacts of AI applications, helping users such as investors assess the materiality of AI use. Moreover, it enables investors to evaluate a company's commitment to responsible AI through structured engagements and thorough assessment of specific risk areas. We have publicly released the framework and toolkit in April 2024, which has received significant attention and positive feedback from the investment community. This paper details each component of the framework, demonstrating its applicability in real-world contexts and its potential to guide ethical AI investments.

cs.AI

QB4AIRA: A Question Bank for AI Risk Assessment

The rapid advancement of Artificial Intelligence (AI), represented by ChatGPT, has raised concerns about responsible AI development and utilization. Existing frameworks lack a comprehensive synthesis of AI risk assessment questions. To address this, we introduce QB4AIRA, a novel question bank developed by refining questions from five globally recognized AI risk frameworks, categorized according to Australia's AI ethics principles. QB4AIRA comprises 293 prioritized questions covering a wide range of AI risk areas, facilitating effective risk assessment. It serves as a valuable resource for stakeholders in assessing and managing AI risks, while paving the way for new risk frameworks and guidelines. By promoting responsible AI practices, QB4AIRA contributes to responsible AI deployment, mitigating potential risks and harms.

cs.SE

Towards Concrete and Connected AI Risk Assessment (C$^2$AIRA): A Systematic Mapping Study

The rapid development of artificial intelligence (AI) has led to increasing concerns about the capability of AI systems to make decisions and behave responsibly. Responsible AI (RAI) refers to the development and use of AI systems that benefit humans, society, and the environment while minimising the risk of negative consequences. To ensure responsible AI, the risks associated with AI systems' development and use must be identified, assessed and mitigated. Various AI risk assessment frameworks have been released recently by governments, organisations, and companies. However, it can be challenging for AI stakeholders to have a clear picture of the available frameworks and determine the most suitable ones for a specific context. Additionally, there is a need to identify areas that require further research or development of new frameworks, as well as updating and maintaining existing ones. To fill the gap, we present a mapping study of 16 existing AI risk assessment frameworks from the industry, governments, and non-government organizations (NGOs). We identify key characteristics of each framework and analyse them in terms of RAI principles, stakeholders, system lifecycle stages, geographical locations, targeted domains, and assessment methods. Our study provides a comprehensive analysis of the current state of the frameworks and highlights areas of convergence and divergence among them. We also identify the deficiencies in existing frameworks and outlines the essential characteristics of a concrete and connected framework AI risk assessment (C$^2$AIRA) framework. Our findings and insights can help relevant stakeholders choose suitable AI risk assessment frameworks and guide the design of future frameworks towards concreteness and connectedness.

cs.SE

A Pattern Language for Blockchain Governance

Blockchain technology has been used to build next-generation applications taking advantage of its decentralised nature. Nevertheless, there are some serious concerns about the trustworthiness of blockchain due to the vulnerabilities in on-chain algorithmic mechanisms, and tedious disputes and debates in off-chain communities. Accordingly, blockchain governance has received great attention for improving the trustworthiness of all decisions that direct a blockchain platform. However, there is a lack of systematic knowledge to guide practitioners to perform blockchain governance. We have performed a systematic literature review to understand the state-of-the-art of blockchain governance. We identify the lifecycle stages of a blockchain platform, and present 14 architectural patterns for blockchain governance in this study. This pattern language can provide guidance for the effective use of patterns for blockchain governance in practice, and support the architecture design of governance-driven blockchain systems.

cs.CR

Operationalizing Human Values in Software Engineering: A Survey

Human values (e.g., pleasure, privacy, and social justice) are what a person or a society considers important. The inability to address them in software-intensive systems can result in numerous undesired consequences (e.g., financial losses) for individuals and communities. Various solutions (e.g., methodologies, techniques) are developed to help "operationalize values in software". The ultimate goal is to ensure building software (better) reflects and respects human values. In this survey, "operationalizing values" is referred to as the process of identifying human values and translating them to accessible and concrete concepts so that they can be implemented, validated, verified, and measured in software. This paper provides a deep understanding of the research landscape on operationalizing values in software engineering, covering 51 primary studies. It also presents an analysis and taxonomy of 51 solutions for operationalizing values in software engineering. Our survey reveals that most solutions attempt to help operationalize values in the early phases (requirements and design) of the software development life cycle. However, the later phases (implementation and testing) and other aspects of software development (e.g., "team organization") still need adequate consideration. We outline implications for research and practice and identify open issues and future research directions to advance this area.

cs.SE

Investigating End-Users' Values in Agriculture Mobile Applications Development: An Empirical Study on Bangladeshi Female Farmers

The omnipresent nature of mobile applications (apps) in all aspects of daily lives raises the necessity of reflecting end-users values (e.g., fairness, honesty, etc.) in apps. However, there are limited considerations of end-users values in apps development. Value violations by apps have been reported in the media and are responsible for end-users dissatisfaction and negative socio-economic consequences. Value violations may bring more severe and lasting problems for marginalized and vulnerable end-users of apps, which have been explored less (if at all) in the software engineering community. However, understanding the values of the end-users of apps is the essential first step towards values-based apps development. This research aims to fill this gap by investigating the human values of Bangladeshi female farmers as a marginalized and vulnerable group of end-users of Bangladeshi agriculture apps. We conducted an empirical study that collected and analyzed data from a survey with 193 Bangladeshi female farmers to explore the underlying factor structure of the values of Bangladeshi female farmers and the significance of demographics on their values. The results identified three underlying factors of Bangladeshi female farmers. The first factor comprises of five values: benevolence, security, conformity, universalism, and tradition. The second factor consists of two values: self-direction and stimulation. The third factor includes three values: power, achievement, and hedonism. We also identified strong influences of demographics on some of the values of Bangladeshi female farmers. For example, area has significant impacts on three values: hedonism, achievement, and tradition. Similarly, there are also strong influences of household income on power and security.

cs.SE

The Impact of Considering Human Values during Requirements Engineering Activities

Human values, or what people hold important in their life, such as freedom, fairness, and social responsibility, often remain unnoticed and unattended during software development. Ignoring values can lead to values violations in software that can result in financial losses, reputation damage, and widespread social and legal implications. However, embedding human values in software is not only non-trivial but also generally an unclear process. Commencing as early as during the Requirements Engineering (RE) activities promises to ensure fit-for-purpose and quality software products that adhere to human values. But what is the impact of considering human values explicitly during early RE activities? To answer this question, we conducted a scenario-based survey where 56 software practitioners contextualised requirements analysis towards a proposed mobile application for the homeless and suggested values-laden software features accordingly. The suggested features were qualitatively analysed. Results show that explicit considerations of values can help practitioners identify applicable values, associate purpose with the features they develop, think outside-the-box, and build connections between software features and human values. Finally, drawing from the results and experiences of this study, we propose a scenario-based values elicitation process -- a simple four-step takeaway as a practical implication of this study.

cs.SE

How Can Human Values Be Addressed in Agile Methods? A Case Study on SAFe

Agile methods are predominantly focused on delivering business values. But can Agile methods be adapted to effectively address and deliver human values such as social justice, privacy, and sustainability in the software they produce? Human values are what an individual or a society considers important in life. Ignoring these human values in software can pose difficulties or risks for all stakeholders (e.g., user dissatisfaction, reputation damage, financial loss). To answer this question, we selected the Scaled Agile Framework (SAFe), one of the most commonly used Agile methods in the industry, and conducted a qualitative case study to identify possible intervention points within SAFe that are the most natural to address and integrate human values in software. We present five high-level empirically-justified sets of interventions in SAFe: artefacts, roles, ceremonies, practices, and culture. We elaborate how some current Agile artefacts (e.g., user story), roles (e.g., product owner), ceremonies (e.g., stand-up meeting), and practices (e.g., business-facing testing) in SAFe can be modified to support the inclusion of human values in software. Further, our study suggests new and exclusive values-based artefacts (e.g., legislative requirement), ceremonies (e.g., values conversation), roles (e.g., values champion), and cultural practices (e.g., induction and hiring) to be introduced in SAFe for this purpose. Guided by our findings, we argue that existing Agile methods can account for human values in software delivery with some evolutionary adaptations.

cs.SE

Human Values in Mobile App Development: An Empirical Study on Bangladeshi Agriculture Mobile Apps

Given the ubiquity of mobile applications (apps) in daily lives, understanding and reflecting end-users' human values (e.g., transparency, privacy, social recognition etc.) in apps has become increasingly important. Violations of end users' values by software applications have been reported in the media and have resulted in a wide range of difficulties for end users. Value violations may bring more and lasting problems for marginalized and vulnerable groups of end-users. This research aims to understand the extent to which the values of Bangladeshi female farmers, marginalized and vulnerable end-users, who are less studied by the software engineering community, are reflected in agriculture apps in Bangladesh. Further to this, we aim to identify possible strategies to embed their values in those apps. To this end, we conducted a mixed-methods empirical study consisting of 13 interviews with app practitioners and four focus groups with 20 Bangladeshi female farmers. The accumulated results from the interviews and focus groups identified 22 values of Bangladeshi female farmers, which the participants expect to be reflected in the agriculture apps. Among these 22 values, 15 values (e.g., accuracy, independence) are already reflected and 7 values (e.g., accessibility, pleasure) are ignored/violated in the existing agriculture apps. We also identified 14 strategies (e.g., "applying human-centered approaches to elicit values", "establishing a dedicated team/person for values concerns") to address Bangladeshi female farmers' values in agriculture apps.

cs.SE

Towards a Human Values Dashboard for Software Development: An Exploratory Study

Background: There is a growing awareness of the importance of human values (e.g., inclusiveness, privacy) in software systems. However, there are no practical tools to support the integration of human values during software development. We argue that a tool that can identify human values from software development artefacts and present them to varying software development roles can (partially) address this gap. We refer to such a tool as human values dashboard. Further to this, our understanding of such a tool is limited. Aims: This study aims to (1) investigate the possibility of using a human values dashboard to help address human values during software development, (2) identify possible benefits of using a human values dashboard, and (3) elicit practitioners' needs from a human values dashboard. Method: We conducted an exploratory study by interviewing 15 software practitioners. A dashboard prototype was developed to support the interview process. We applied thematic analysis to analyse the collected data. Results: Our study finds that a human values dashboard would be useful for the development team (e.g., project manager, developer, tester). Our participants acknowledge that development artefacts, especially requirements documents and issue discussions, are the most suitable source for identifying values for the dashboard. Our study also yields a set of high-level user requirements for a human values dashboard (e.g., it shall allow determining values priority of a project). Conclusions: Our study suggests that a values dashboard is potentially used to raise awareness of values and support values-based decision-making in software development. Future work will focus on addressing the requirements and using issue discussions as potential artefacts for the dashboard.

cs.SE

Measuring Bangladeshi Female Farmers' Values for Agriculture Mobile Applications Development

The ubiquity of mobile applications (apps) in daily life raises the imperative that the apps should reflect users' values. However, users' values are not usually taken into account in app development. Thus there is significant potential for user dissatisfaction and negative socio-economic consequences. To be cognizant of values in apps, the first step is to find out what those values are, and that was the objective of this study conducted in Bangladesh. Our focus was on rural women, specifically female farmers. The basis for our study was Schwartz's universal human values theory, and we used an associated survey instrument, the Portrait Values Questionnaire (PVQ). Our survey of 193 Bangladeshi female farmers showed that Conformity and Security were regarded as the most important values, while Power, Hedonism, and Stimulation were the least important. This finding would be helpful for developers to take into account when developing agriculture apps for this market. In addition, the methodology we used provides a model to follow to elicit the values of apps' users in other communities.

cs.CY

A Study on the Prevalence of Human Values in Software Engineering Publications, 2015-2018

Failure to account for human values in software (e.g., equality and fairness) can result in user dissatisfaction and negative socio-economic impact. Engineering these values in software, however, requires technical and methodological support throughout the development life cycle. This paper investigates to what extent software engineering (SE) research has considered human values. We investigate the prevalence of human values in recent (2015 - 2018) publications at some of the top-tier SE conferences and journals. We classify SE publications, based on their relevance to different values, against a widely used value structure adopted from social sciences. Our results show that: (a) only a small proportion of the publications directly consider values, classified as relevant publications; (b) for the majority of the values, very few or no relevant publications were found; and (c) the prevalence of the relevant publications was higher in SE conferences compared to SE journals. This paper shares these and other insights that motivate research on human values in software engineering.

cs.SE