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61 |
Addressing AI ethics through codification
پرداختن به اخلاق هوش مصنوعی از طریق تدوین-2020 AI ethics rapidly becomes one of the most
significant issues in assessing the impact of AI on social
welfare and development. A technology that does not meet
the ethical criteria of a society is likely to face a long and
hard process of acceptance regardless of its potentially
tremendous positive potential for long-term socio-economic
development. The development of artificial intelligence (AI)
technologies is undoubtedly associated with the need to
answer ethical questions, and the perception of AI in society
will be largely determined by compliance with ethical
criteria, whether written or not. At the same time, AI as a
technological system itself does not have a natural ethical
content; the authors believe that in practice ethical concerns
may be addressed by means of ethical codes and compliance
rules that articulate what constitutes ethical behaviour in
specific areas of application of AI systems. Such a set of rules
(a code for AI ethics) could be followed by all actors
throughout the complete lifecycle of the system starting with
the design stage. The specification of general ethical
principles as industry-specific codes of practice would also
facilitate classification, evaluation and measurement of
systems, both at the technical level and at the level of public
perception and trust. The article considers examples of codification of ethical
principles and offers several approaches for practical use in
solving issues of ethics in the field of AI at the national and
international level. Keywords: ethics | AI | codification | regulation | standards | responsibility | bias | trustworthiness | personal data protection | international cooperation in AI | soft regulation |
مقاله انگلیسی |
62 |
Trustworthy AI Development Guidelines for Human System Interaction
دستورالعمل های قابل اعتماد توسعه هوش مصنوعی برای تعامل سیستم انسانی-2020 Artificial Intelligence (AI) is influencing almost all
areas of human life. Even though these AI-based systems frequently
provide state-of-the-art performance, humans still hesitate
to develop, deploy, and use AI systems. The main reason for
this is the lack of trust in AI systems caused by the deficiency of
transparency of existing AI systems. As a solution, “Trustworthy
AI” research area merged with the goal of defining guidelines
and frameworks for improving user trust in AI systems, allowing
humans to use them without fear. While trust in AI is an active
area of research, very little work exists where the focus is to
build human trust to improve the interactions between human
and AI systems. In this paper, we provide a concise survey on
concepts of trustworthy AI. Further, we present trustworthy AI
development guidelines for improving the user trust to enhance
the interactions between AI systems and humans, that happen
during the AI system life cycle. Index Terms: Trustworthy AI | Transparency | Explainable AI | Human System Interactions | Human Machine Interactions | AI Life Cycle |
مقاله انگلیسی |
63 |
Build confidence and acceptance of AI-based decision support systems - Explainable and liable AI
اعتماد به نفس و پذیرش مبتنی بر هوش مصنوعی ایجاد کنید سیستم های پشتیبانی تصمیم - هوش مصنوعی قابل توضیح و مسئولیت پذیر-2020 Artificial Intelligence has known an incredible
development since 2012. It was due to the impressive
improvement of sensors, data quality and quantity, storage and
computing capacity, etc. The promises AI offered led many
scientific domains to implement AI-based decision support tool.
However, despite numerous amazing results, very serious
failures have raised Human mistrust, fear and scorn against AI.
In Industries, staff members cannot afford to use tools that
might fail them. This is especially true for Transportation
operators where security and safety are at risk. Then, the
question that arises is how to build Human confidence and
acceptance of AI-based decision support system. In this paper,
we combine different points of view to propose a structured
overview of Transparency, Explicability and Interpretability,
with new definitions arising as a consequence. Then we discuss
the need for understandable information from the AI system, to
legitimate or refute the tool’s proposal. To conclude we offer
ethical reflexions and ideas to develop confidence in AI. Keywords: explainable AI | liable AI | decision support system | confidence | technology |
مقاله انگلیسی |
64 |
Z-number based earned value management (ZEVM): A novel pragmatic contribution towards a possibilistic cost-duration assessment
مدیریت ارزش به دست آمده مبتنی بر عدد Z (ZEVM): سهم عملگرا جدید نسبت به ارزیابی هزینه تمام شده احتمالی-2020 The Earned value management (EVM) is one of the simplified analytical cost-duration assessment tools which
assist project managers in monitoring the status of the project undertaken. The EVM has been elaborated by both
deterministic and uncertain numbers such as fuzzy logic in the light of time. Even though cost-duration analysis
is so sensitive and fluctuating in projects, the adopted approaches were unable to consider the conspicuous
unreliability which is always involving the decision-making data. This problem impedes project managers to
trust the foreseen inferences. To help in overcoming this critical deficiency, Z-numbers were proposed to take
possibilities and reliabilities into account. Applying Z-numbers and possibilistic modeling in the EVM is a
challenging topic which causes the accuracy of cost-duration tracing results to be significantly enhanced. This
paper presents the application of z-numbers for modeling the earned value indicators and proves the superiority
of the ZEVM against traditional fuzzy EVM. This work originally adds to the state-of-the-art literature on earned
value management by presenting a proposal and applications of a new as Z-Earned Value Management (ZEVM).
An illustrative case is resolved to magnify the capability of the proposed framework in dealing with higher levels
of uncertainty associated with decision-making data. Keywords: Earned value management | Fuzzy sets | Project evaluation | Uncertainty | Z-number |
مقاله انگلیسی |
65 |
“Its like super structural” – Overdose experiences of youth who use drugs and police in three non-metropolitan cities across British Columbia
"این مانند ساختاری فوق العاده است" - تجربیات بیش از حد مصرف جوانان در سه شهر غیر کلانشهر بریتیش کلمبیا که از مواد مخدر و پلیس استفاده می کنند-2020 Introduction: Youth who use drugs (YWUD) are vulnerable to experience or encounter drug related overdose
deaths. Fentanyl has increased the risks, calling greater attention to overdose. In response, there have been
increases in harm reduction services and policies such as the Good Samaritan Drug Overdose Act (GSDOA) which
exempts people who witness an overdose and call 9–1–1 from being charged for possession of drugs. However,
fear of police continues to be a barrier to calling 9–1–1. This paper focuses on the experiences of youth with
police in overdose situations and their knowledge of GSDOA.
Methods: Youth, aged 16–30, who had used drugs at least weekly, and had encountered police in the past year
were recruited between May 2017 and June 2018 in three non-metropolitan cities in British Columbia, Canada.
38 participants completed qualitative interviews asking them about their experiences with police, overdose,
decisions to call 9–1–1, and their understanding of the GSDOA. Their responses were coded in NVIVO and
analyzed using interpretive description.
Results: For many YWUD in this study, overdoses are an ever-present part of their lives and fear of fentanyl has
left them concerned for themselves and others. Negative experiences occurred when police used their power
without benefit to youth or were rough or disrespectful, without care for the person overdosing. Youth saw
police in a positive light if they were compassionate, stepping aside for paramedics or reviving someone experiencing
an overdose. Youth had very mixed knowledge of the GSDOA and were concerned about criminalization
if they called 9–1–1.
Conclusions: Collaboration with police and local stakeholders is required to address the concerns of YWUD and
to increase awareness and penetration of policies such as the GSDOA. Changes to policing cultures that prioritize
health rather than criminalize YWUD may increase youths trust of police and increase calls to 9–1–1. Keywords: Drug overdose | Youth who use drugs | Police discretion | Naloxone | Harm reduction |
مقاله انگلیسی |
66 |
امضای کوانتومی مبتنی بر هویت بر پایه حالات بل
سال انتشار: 2020 - تعداد صفحات فایل pdf انگلیسی: 8 - تعداد صفحات فایل doc فارسی: 17 براساس حالت های بل، یک طرح امضای کوانتومی مبتنی بر هویت پیشنهاد شده است. در طرح ما، کلید مخصوص امضا کننده توسط یک شخص ثالث قابل اعتماد به نام تولید کننده کلید خصوصی (PKG) تولید میشود، در حالی که کلید عمومی امضا کننده هویت او (مرد)/او (زن) (مانند نام او یا آدرس ایمیل) است. پیغامی که باید امضا شود به ترتیب کد حالت های بل کدگذاری (رمزنگاری) میشود. برای ایجاد امضای کوانتومی، امضا کننده توالی حالت بل را با کلید خصوصی او (مرد)/او (زن) امضا میکند. امضای کوانتومی را می توان توسط هر کسی با هویت امضا کننده تایید کرد. طرح امضای کوانتومی ما از مزایای طرح امضای کلاسیک مبتنی بر هویت برخوردار است. نیازی به استفاده از حافظه کوانتومی بلند مدت ندارد. از سوی دیگر، در طرح ما، در طول مرحله تایید امضا، بازبینی کننده نیازی به انجام هیچ آزمون مبادله ی کوانتومی ندارد. در طرح ما، تولید کننده کلید خصوصی یا PKG میتواند سبب از دست دادن امضای کوانتومی شود که در بسیاری از طرحهای امضا کوانتومی قابلاجرا نیست. طرح ما همچنین دارای ویژگیهای امنیتی غیرانکار و غیر قابل جعل و غیره است. امضای ما مطمئنتر، کارآمد و عملی تر از طرح های مشابه دیگر است.
کلمات کلیدی: امضای کوانتومی | امضای مبتنی بر هویت | حالت بل | آزمون کوانتومی مبادله ای |
مقاله ترجمه شده |
67 |
Productive employment and decent work: The impact of AI adoption on psychological contracts, job engagement and employee trust
اشتغال مولد و کار مناسب: تأثیر پذیرش هوش مصنوعی در قراردادهای روانشناختی ، مشاغل شغلی و اعتماد کارمندان-2020 This research examines the tension between the aims of the United Nations’ Sustainable Development Goal 8
(SDG 8), to promote productive employment and decent work, and the adoption of Artificial Intelligence (AI).
Our findings are based on the analysis of 232 survey results, where we tested the effects of AI adoption on
workers’ psychological contract, engagement and trust. We find that psychological contracts had a significant,
positive effect on job engagement and on trust. Yet, with AI adoption, the positive effect of psychological
contracts fell significantly. A further re-examination of the extant literature leads us to posit that AI adoption
fosters the creation of a third type of psychological contract, which we term “Alienational”. Whereas SDG 8 is
premised on strengthening relational contracts between an organization and its employees, the adoption of AI
has the opposite effect, detracting from the very nature of decent work. Keywords: Artificial intelligence | Psychological contract | Employee engagement | Job trust | Sustainable development goals | Decent work |
مقاله انگلیسی |
68 |
Drivers, barriers and social considerations for AI adoption in business and management: A tertiary study
رانندگان ، موانع و ملاحظات اجتماعی برای پذیرش هوش مصنوعی در تجارت و مدیریت: یک مطالعه عالی-2020 The number of academic papers in the area of Artificial Intelligence (AI) and its applications across business and
management domains has risen significantly in the last decade, and that rise has been followed by an increase in
the number of systematic literature reviews.
The aim of this study is to provide an overview of existing systematic reviews in this growing area of research
and to synthesise the findings related to drivers, barriers and social implications of the AI adoption in business
and management.
The methodology used for this tertiary study is based on Kitchenham and Charter’s guidelines [14], resulting
in a selection of 30 reviews published between 2005 and 2019 which are reporting results of 2021 primary
studies.
These reviews cover the AI adoption across various business sectors (healthcare, information technology,
energy, agriculture, apparel industry, engineering, smart cities, tourism and transport), management and business
functions (HR, customer services, supply chain, health and safety, project management, decision-support,
systems management and technology adoption).
While the drivers for the AI adoption in these areas are mainly economic, the barriers are related to the
technical aspects (e.g. availability of data, reusability of models) as well as the social considerations such as,
increased dependence on non-humans, job security, lack of knowledge, safety, trust and lack of multiple
stakeholders’perspectives.
Very few reviews outside of the healthcare management domain consider human, organisational and wider
societal factors of the AI adoption.
In addition to increased focus on social implications of AI, the reviews are recommending more rigorous
evaluation, increased use of hybrid solutions (AI and non-AI) and multidisciplinary approach to AI design and
evaluation.
Furthermore, this study found that there is a lack of systematic reviews in some of the early AI adoption sectors
such as financial industry and retail. Keywords: Artificial intelligence | Business | Machine learning | Management | Systematic literature review | Tertiary study |
مقاله انگلیسی |
69 |
Reduced Demand Uncertainty and the Sustainability of Collusion: How AI Could Affect Competition
کاهش عدم اطمینان تقاضا و پایداری تبانی: چگونه هوش مصنوعی می تواند بر رقابت تأثیر بگذارد-2020 We model how a technology that perfectly predicts one of two stochastic demand shocks alters the character
and sustainability of collusion. Our results show that mechanisms that reduce firms’ uncertainty about the
true level of demand have ambiguous welfare implications for consumers and firms alike. An exogenous
improvement in firms’ ability to predict demand may make collusion possible where it was previously unsustainable
or more profitable where it previously existed. However, an increase in transparency also may make
collusion impracticable where it had been possible. The intuition for this ambiguity is that greater clarity
about the true state of demand raises the payoffs both to colluding and to cheating. Our findings on the ambiguous
welfare implications of reduced uncertainty contribute to the emerging literature on how algorithms,
artificial intelligence (AI), and “big data” in market intelligence applications may affect competition. Keywords: Artificial Intelligence | Uncertainty | Collusion | Price Discrimination | Antitrust |
مقاله انگلیسی |
70 |
Do hybrids impede sustainability? How semantic reorientations and governance reforms can produce and preserve sustainability in sharing business models
آیا هیبریدها مانع پایداری می شوند؟ اصلاح مجدد معنایی و اصلاحات حکومتی چگونه می توانند پایداری را در به اشتراک گذاری مدل های تجاری ایجاد و حفظ کنند-2020 The sharing economy is a hotbed of hybridity and sustainability owing to the reduction in transactions costs that create information, trust, and trade. However, the hybridization also challenges the sustainability of sharing business models, a tension often criticized but rarely addressed. This paper identifies and solves three challenges of hybridization. First, we show that there is no deterministic link between organizational missions and sustainability outcomes. This means that not-for-profits or social businesses are not necessarily more sustainable than for-profits. Second, all business models set different default goal priorities, but face the same governance challenge of achieving sustainability. Third, to meet this challenge, all business models can use the same governance strategies of creating value—rule reforms that implement credible commitments to overcome social dilemmas. Understanding and managing these three hybridity challenges are an essential task for the strategic management of sustainable business models in the sharing economy. Keywords: Sharing economy | Business models | Governance | Hybrids | Sustainability |
مقاله انگلیسی |