The ethics of designing artificial agents

In their important paper “Autonomous Agents”, Floridi and Sanders use “levels of abstraction” to argue that computers are or may soon be moral agents. In this paper we use the same levels of abstraction to illuminate differences between human moral agents and computers. In their paper, Floridi and Sanders contributed definitions of autonomy, moral accountability and responsibility, but they have not explored deeply some essential questions that need to be answered by computer scientists who design artificial agents. One such question is, “Can an artificial agent that changes its own programming become so autonomous that the original designer is no longer responsible for the behavior of the artificial agent?” To explore this question, we distinguish between LoA1 (the user view) and LoA2 (the designer view) by exploring the concepts of unmodifiable, modifiable and fully modifiable tables that control artificial agents. We demonstrate that an agent with an unmodifiable table, when viewed at LoA2, distinguishes an artificial agent from a human one. This distinction supports our first counter-claim to Floridi and Sanders, namely, that such an agent is not a moral agent, and the designer bears full responsibility for its behavior. We also demonstrate that even if there is an artificial agent with a fully modifiable table capable of learning* and intentionality* that meets the conditions set by Floridi and Sanders for ascribing moral agency to an artificial agent, the designer retains strong moral responsibility.     

From human resources to human rights: Impact assessments for hiring algorithms

Ethics and Information Technology - Over the years, companies have adopted hiring algorithms because they promise wider job candidate pools, lower recruitment costs and less human bias. Despite...     

OK computer: Worker perceptions of algorithmic recruitment

We provide evidence on how workers on an online platform perceive algorithmic versus human recruitment through two incentivized experiments designed to elicit willingness to pay for human or algorithmic evaluation. In particular, we test how information on workers’ performance affects their recruiter choice and whether the algorithmic recruiter is perceived as more or less gender-biased than the human one. We find that workers do perceive human and algorithmic evaluation differently, even though both recruiters are given the same inputs in our controlled setting. Specifically, human recruiters are perceived to be more error-prone evaluators and place more weight on personal characteristics, whereas algorithmic recruiters are seen as placing more weight on task performance. Consistent with these perceptions, workers with good task performance relative to others prefer algorithmic evaluation, whereas those with lower task performance prefer human evaluation. We also find suggestive evidence that perceived differences in gender bias drive preferences for human versus algorithmic recruitment.     

科技型企业的人才资源管理模式创新

分析了科技型企业人才资源的特点,提出科技型企业人力资源开发、管理都有别于一般的人力资源开发与管理。科技型企业人力资源管理组织结构的设计,必须充分考虑知识型员工的特点及其需求。对知识型员工的激励,应以发展与成长为主,提升服务在人力资源管理中的重要地位,强调企业文化、沟通交流环境以及信任、承诺、尊重、自主、支持、创新、学习、合作、支援、授权和公正等人力资源管理新准则。人才创新管理模式要树立“创新人”的新理念,营造相互尊重及和谐的工作环境,改革管理制度形成完善的激励机制。     

珠三角招聘HR从业者的要求性指标的统计分析——以招聘、薪酬、绩效、培训四类专员为例

本文通过对招聘HR从业者的招聘广告进行统计,对从事不同岗位工作的HR从业者的要求性指标进行分析,结果显示出,HR从业者都要求具备较高的学历,经验,专业知识,沟通能力及个性要求。但不同的岗位从业者有个自的特点,招聘专员要求较高的渠道拓展能力,薪酬福利专员要求较高的统计知识,绩效考核专员要求较高的分析判断能力,培训专员要求较高的表达能力和课程开发能力。由此,可以为有志于从事不同岗位的HR从业者指明能力培养的方向,为企业招聘不同岗位的HR从业者提供一定的借鉴,为在职者完善自身能力提供一定的参考,同时,也希望能在人力资源管理的专业化道路上起到抛砖引玉的作用。     

The “big red button” is too late: an alternative model for the ethical evaluation of AI systems

As a way to address both ominous and ordinary threats of artificial intelligence (AI), researchers have started proposing ways to stop an AI system before it has a chance to escape outside control and cause harm. A so-called “big red button” would enable human operators to interrupt or divert a system while preventing the system from learning that such an intervention is a threat. Though an emergency button for AI seems to make intuitive sense, that approach ultimately concentrates on the point when a system has already “gone rogue” and seeks to obstruct interference. A better approach would be to make ongoing self-evaluation and testing an integral part of a system’s operation, diagnose how the system is in error and to prevent chaos and risk before they start. In this paper, we describe the demands that recent big red button proposals have not addressed, and we offer a preliminary model of an approach that could better meet them. We argue for an ethical core (EC) that consists of a scenario-generation mechanism and a simulation environment that are used to test a system’s decisions in simulated worlds, rather than the real world. This EC would be kept opaque to the system itself: through careful design of memory and the character of the scenario, the system’s algorithms would be prevented from learning about its operation and its function, and ultimately its presence. By monitoring and checking for deviant behavior, we conclude, a continual testing approach will be far more effective, responsive, and vigilant toward a system’s learning and action in the world than an emergency button which one might not get to push in time.     

招聘活动中的双向营销行为分析

市场营销不仅仅是一种企业职能,还是一种观念、一种意识、一种看待问题的方式.本文从市场营销经典理论--4P'S的角度出发来研究企业和求职者之间的招聘活动,并据此对招聘、应聘活动中的营销策略进行分析.具体通过招聘方和应聘方在产品策略、价格策略、渠道策略和促销策略中的行为进行对比分析,为招聘方得到最适合的人才提供指导,同时为应聘方能找到最合适的工作提供建议.     

Exploring human resource management intelligence practices using machine learning models

The use of machine learning for recruitment has become one of the main themes in human resources ever since machine learning software investigated the first recruitment software and discovered that utilizing technology improves their effectiveness at work, speed, and makes the process simpler. In order to better handle employee files, profiles, turnover, data analytics, and the creation of electronic personal data sheets for government service records, a human resource information system that incorporates machine learning has been created. Using a supervised machine learning technique, it was designed to foresee staff turnover. From a theoretical perspective, machine learning apps may be able to perform the same tasks as HR specialists, if not better or faster. Supporting HR professionals in becoming a true business partner and providing them with accurate and reliable advice, the interaction between HR professionals and line top management believes that the HR professionals still has surplus over machine learning, alone. Human resources methods and the significance of machine learning are the primary focus of this paper. This paper's three goals are to (1) determine how much of an impact Machine learning can have on the organization's recruitment procedures, (2) examine the extent to which this technology has been adopted, and (3) examine the frequency with which complaints have been lodged during these crucial exercises.     

Un-making artificial moral agents

Floridi and Sanders, seminal work, “On the morality of artificial agents” has catalyzed attention around the moral status of computer systems that perform tasks for humans, effectively acting as “artificial agents.” Floridi and Sanders argue that the class of entities considered moral agents can be expanded to include computers if we adopt the appropriate level of abstraction. In this paper we argue that the move to distinguish levels of abstraction is far from decisive on this issue. We also argue that adopting certain levels of abstraction out of context can be dangerous when the level of abstraction obscures the humans who constitute computer systems. We arrive at this critique of Floridi and Sanders by examining the debate over the moral status of computer systems using the notion of interpretive flexibility. We frame the debate as a struggle over the meaning and significance of computer systems that behave independently, and not as a debate about the ‘true’ status of autonomous systems. Our analysis leads to the conclusion that while levels of abstraction are useful for particular purposes, when it comes to agency and responsibility, computer systems should be conceptualized and identified in ways that keep them tethered to the humans who create and deploy them.     

Human resources for Big Data professions: A systematic classification of job roles and required skill sets

The rapid expansion of Big Data Analytics is forcing companies to rethink their Human Resource (HR) needs. However, at the same time, it is unclear which types of job roles and skills constitute this area. To this end, this study pursues to drive clarity across the heterogeneous nature of skills required in Big Data professions, by analyzing a large amount of real-world job posts published online. More precisely we: 1) identify four Big Data ‘job families’; 2) recognize nine homogeneous groups of Big Data skills (skill sets) that are being demanded by companies; 3) characterize each job family with the appropriate level of competence required within each Big Data skill set. We propose a novel, semi-automated, fully replicable, analytical methodology based on a combination of machine learning algorithms and expert judgement. Our analysis leverages a significant amount of online job posts, obtained through web scraping, to generate an intelligible classification of job roles and skill sets. The results can support business leaders and HR managers in establishing clear strategies for the acquisition and the development of the right skills needed to leverage Big Data at best. Moreover, the structured classification of job families and skill sets will help establish a common dictionary to be used by HR recruiters and education providers, so that supply and demand can more effectively meet in the job marketplace.     

IBM's Chess Players: On AI and Its Supplements

This article investigates the ways in which the reporting of technological developments in artificial intelligence (AI) can serve as occasions in which Occidental modernity's cultural antinomies are played out. It takes as its reference point the two chess tournaments (in 1996 and 1997) between the then world champion Gary Kasparov and the IBM dedicated chess computers Deep Blue and Deeper Blue and shows how these games of chess came to be seen as an arena where fundamental issues pertaining to human identity were contested. The article considers the dominant framing of these encounters in terms of a conflict between two opposed categories—“human” and “machine”—and argues the essential role of human agency, the human supplement, in the performances of machine intelligence.     

Testing the contribution of multi-skilled employees to the financial performance of high-tech organizations

This paper presents a study that found no support for the claim: “Employees with multiple skills enable organizations to thrive in dynamically changing and unpredictable environments.” The study showed that the “multi-skilled worker” (MSW) was a non-significant predictor of financial performance in a statistical analysis of companies that operated in these environments. A sample of companies drawn from three high-technology industries (suppliers to the automotive industry, electronic instrumentation, and semiconductor manufacturers) showed no relationship between employee skill diversity and financial performance. As a result, it appears that the benefits of a multi-skilled workforce may be overstated in terms of its contribution to the organization's financial performance. Or, it may simply suggest that the additional profits generated by responsive, multi-skilled employees are insufficient to offset the additional costs associated with training and hiring them. Companies should be aware of these issues when considering plans to expand employee skill sets as part of a strategy for improving responsiveness.     

Real moral problems in the use of virtual reality

In this paper, we argue that, under a specific set of circumstances, designing and employing certain kinds of virtual reality (VR) experiences can be unethical. After a general discussion of simulations and their ethical context, we begin our argument by distinguishing between the experiences generated by different media (text, film, computer game simulation, and VR simulation), and argue that VR experiences offer an unprecedented degree of what we call “perspectival fidelity” that prior modes of simulation lack. Additionally, we argue that when VR experiences couple this perspectival fidelity with what we call “context realism,” VR experiences have the ability to produce “virtually real experiences.” We claim that virtually real experiences generate ethical issues for VR technologies that are unique to the medium. Because subjects of these experiences treat them as if they were real, a higher degree of ethical scrutiny should be applied to any VR scenario with the potential to generate virtually real experiences. To mitigate this unique moral hazard, we propose and defend what we call “The Equivalence Principle.” This principle states that “if it would be wrong to allow subjects to have a certain experience in reality, then it would be wrong to allow subjects to have that experience in a virtually real setting.” We argue that such a principle, although limited in scope, should be part of the risk analysis conducted by any Institutional Review Boards, psychologists, empirically oriented philosophers, or game designers who are using VR technology in their work.     

城乡融合对中国农业碳排放效率的影响及其机制

【目的】城乡融合作为农业生产要素配置效率提升的重要手段,是影响农业碳排放效率的关键因素。【方法】本文采用中国2005—2020年省域面板数据,在测度城乡融合发展水平和农业碳排放效率的基础上,综合运用固定效应模型、空间自回归模型和门槛效应模型探究了城乡融合发展对农业碳排放效率的影响效果及其作用机制。【结果】研究发现：①总体上,城乡融合发展指数对农业碳排放效率具有显著的负向影响。机制检验表明,城乡融合发展有助于提升农业低碳技术效率,但对前沿技术进步具有显著负向影响,进而不利于改善农业碳排放效率。上述研究结论在空间溢出视角下仍然成立。②从城乡融合发展的不同维度来看,“人的融合”能够通过改善技术效率来有效提升农业碳排放效率,而“地的融合”和“资本的融合”虽然对技术效率均具有正向影响,但由于受到技术进步的负向制约,最终阻碍了农业碳排放效率的总体提升。③门槛计量分析发现,地区经济发展水平是约束城乡融合发展和农业碳排放效率关系的显著门槛变量,当地区经济发展水平迈过阈值后,城乡融合发展能够对农业碳排放效率产生显著的提升效应。【结论】因此,地方政府在推进城乡融合发展过程中,应兼顾地区经济发展水平,着力构建以“人”为核心,统筹“地”和“资本”融合的城乡融合体系与机制,为以推动城乡协调发展为契机来实现低碳农业高质量发展创造条件。     

Deletion as second death: the moral status of digital remains

There has been increasing attention in sociology and internet studies to the topic of ‘digital remains’: the artefacts users of social network services (SNS) and other online services leave behind when they die. But these artefacts also pose philosophical questions regarding what impact, if any, these artefacts have on the ontological and ethical status of the dead. One increasingly pertinent question concerns whether these artefacts should be preserved, and whether deletion counts as a harm to the deceased user and therefore provides pro tanto reasons against deletion. In this paper, I build on previous work invoking a distinction between persons and selves to argue that SNS offer a particularly significant material instantiation of persons. The experiential transparency of the SNS medium allows for genuine co-presence of SNS users, and also assists in allowing persons (but not selves) to persist as ethical patients in our lifeworld after biological death. Using Blustein’s “rescue from insignificance” argument for duties of remembrance, I argue that this persistence function supplies a nontrivial (if defeasible) obligation not to delete these artefacts. Drawing on Luciano Floridi’s account of “constitutive” information, I further argue that the “digital remains” metaphor is surprisingly apt: these artefacts in fact enjoy a claim to moral regard akin to that of corpses.     

Supporting “Everyday Analysts” in Safety- and Time-Critical Situations

The need for quick, timely, and accurate information is critical in emergency events. During mass emergencies, people assemble information from both official and unofficial sources. As digital access expands, people will increasingly incorporate information from digital sources into decision making and assess it against the local circumstances they experience. If we extrapolate what such behavior means for the future, we can see that information management under emergency conditions will need to become increasingly socially distributed. The key question then is how to assess the quality of information: how “good” or “bad” it is; whether it is “misinformation” or “disinformation.” Borrowing from Simon's notion of satisficing, the authors argue that people's assessment of information helpfulness and credibility is a function of the “everyday analytic” skills they employ during mass emergencies. To facilitate the critical work of “everyday analysts,” we outline a research agenda for the development of analytical support tools.     

The amoralist challenge to gaming and the gamer’s moral obligation

According to the amoralist, computer games cannot be subject to moral evaluation because morality applies to reality only, and games are not real but “just games”. This challenges our everyday moralist intuition that some games are to be met with moral criticism. I discuss and reject the two most common answers to the amoralist challenge and argue that the amoralist is right in claiming that there is nothing intrinsically wrong in simply playing a game. I go on to argue for the so-called “endorsement view” according to which there is nevertheless a sense in which games themselves can be morally problematic, viz. when they do not only represent immoral actions but endorse a morally problematic worldview. Based on the endorsement view, I argue against full blown amoralism by claiming that gamers do have a moral obligation when playing certain games even if their moral obligation is not categorically different from that of readers and moviegoers.     

From swiping to casual sex and/or committed relationships: Exploring the experiences of Tinder users

To better understand if and how the mechanics of the process Tinder imposes on its users (i.e., swiping, matching, and starting conversations) influences the resulting sexual or romantic interactions, we collected data from 1038 Belgian Tinder users. Our findings show that a user's swiping quantity does not guarantee a higher number of Tinder matches, women have generally more matches than men and men usually have to start a conversation on Tinder. Moreover, while conversations were positively associated with reported offline Tinder encounters, less than half of our sample reported having had an offline meeting with another Tinder user. Whereas more than one third of these offline encounters led to casual sex, more than a quarter resulted in the formation of a committed relationship. Such findings indicate that Tinder is not “just a hookup app”, as often assumed in public discourse. We argue it is plausible that sexual encounters will eventually lead to committed relationships in a society where initiation of relationship formation with dating has been replaced by hooking up.     

Computers in control: Rational transfer of authority or irresponsible abdication of autonomy?

To what extent should humans transfer, or abdicate, “responsibility” to computers? In this paper, I distinguish six different senses of ‘responsible’ and then consider in which of these senses computers can, and in which they cannot, be said to be “responsible” for “deciding” various outcomes. I sort out and explore two different kinds of complaint against putting computers in greater “control” of our lives: (i) as finite and fallible human beings, there is a limit to how far we can acheive increased reliability through complex devices of our own design; (ii) even when computers are more reliable than humans, certain tasks (e.g., selecting an appropriate gift for a friend, solving the daily crossword puzzle) are inappropriately performed by anyone (or anything) other than oneself. In critically evaluating these claims, I arrive at three main conclusions: (1) While we ought to correct for many of our shortcomings by availing ourselves of the computer's larger memory, faster processing speed and greater stamina, we are limited by our own finiteness and fallibility (rather than by whatever limitations may be inherent in silicon and metal) in the ability to transcend our own unreliability. Moreover, if we rely on programmed computers to such an extent that we lose touch with the human experience and insight that formed the basis for their programming design, our fallibility is magnified rather than mitigated. (2) Autonomous moral agents can reasonably defer to greater expertise, whether human or cybernetic. But they cannot reasonably relinquish “background-oversight” responsibility. They must be prepared, at least periodically, to review whether the “expertise” to which they defer is indeed functioning as he/she/it was authorized to do, and to take steps to revoke that authority, if necessary. (3) Though outcomes matter, it can also matter how they are brought about, and by whom. Thus, reflecting on how much of our lives should be directed and implemented by computer may be another way of testing any thoroughly end-state or consequentialist conception of the good and decent life. To live with meaning and purpose, we need to actively engage our own faculties and empathetically connect up with, and resonate to, others. Thus there is some limit to how much of life can be appropriately lived by anyone (or anything) other than ourselves.