Progress in the field of artificial intelligence has been accelerating rapidly in the past two decades. Various autonomous systems from purely digital ones to autonomous vehicles are being developed and deployed out on the field. As these systems exert a growing impact on society, ethics in relation to artificial intelligence and autonomous systems have recently seen growing attention among the academia. However, the current literature on the topic has focused almost exclusively on theory and more specifically on conceptualization in the area. To widen the body of knowledge in the area, we conduct an empirical study on the current state of practice in artificial intelligence ethics. We do so by means of a multiple case study of five case companies, the results of which indicate a gap between research and practice in the area. Based on our findings we propose ways to tackle the gap.

Word embedding spaces are powerful tools for capturing latent semantic relationships between terms in corpora, and have become widely popular for building state-of-the-art natural language processing algorithms. However, studies have shown that societal biases present in text corpora may be incorporated into the word embedding spaces learned from them. Thus, there is an ethical concern that human-like biases contained in the corpora and their derived embedding spaces might be propagated, or even amplified with the usage of the biased embedding spaces in downstream applications. In an attempt to quantify these biases so that they may be better understood and studied, several bias metrics have been proposed. We explore the statistical properties of these proposed measures in the context of their cited applications as well as their supposed utilities. We find that there are caveats to the simple interpretation of these metrics as proposed. We find that the bias metric proposed by Bolukbasi et al. 2016 is highly sensitive to embedding hyper-parameter selection, and that in many cases, the variance due to the selection of some hyper-parameters is greater than the variance in the metric due to corpus selection, while in fewer cases the bias rankings of corpora vary with hyper-parameter selection. In light of these observations, it may be the case that bias estimates should not be thought to directly measure the properties of the underlying corpus, but rather the properties of the specific embedding spaces in question, particularly in the context of hyper-parameter selections used to generate them. Hence, bias metrics of spaces generated with differing hyper-parameters should be compared only with explicit consideration of the embedding-learning algorithms particular configurations.

Background: Despite a long history, numerous laws and regulations, ethics remains an unnatural topic for many software engineering researchers. Poor research ethics may lead to mistrust of research results, lost funding and retraction of publications. A core principle for research ethics is confidentiality, and anonymization is a standard approach to guarantee it. Many guidelines for qualitative software engineering research, and for qualitative research in general, exist, but these do not penetrate how and why to anonymize interview data. Aims: In this paper we aim to identify ethical guidelines for software engineering interview studies involving industrial practitioners. Method: By learning from previous experiences and listening to the authority of existing guidelines in the more mature field of medicine as well as in software engineering, a comprehensive set of checklists for interview studies was distilled. Results: The elements of an interview study were identified and ethical considerations and recommendations for each step were produced, in particular with respect to anonymization. Important ethical principles are: consent, beneficence, confidentiality, scientific value, researcher skill, justice, respect for law, and ethical reviews. Conclusions: The most important contribution of this study is the set of checklists for ethical interview studies. Future work is needed to refine these guidelines with respect to legal aspects and ethical boards.

The chief research officer of the Seattle Indian Health Board is creating programs and databases that are not based on Western concepts to better serve indigenous communities.

This blog is a summary of an interesting internal discussion we had among analysts. I’d like to extend my thanks to Brigitte Majewski, Martha Bennett, Sucharita Kodali, Benjamin Ensor, and Fatemeh Khatibloo, who all helped with the thinking. I’m merely putting the pieces together for you here, because connecting the dots is where I come in at Forrester . . .

Mobility is the backbone of urban life and a vital economic factor in the development of the world. Rapid urbanization and the growth of mega-cities is bringing dramatic changes in the capabilities of vehicles. Innovative solutions like autonomy, electrification, and connectivity are on the horizon. How, then, we can provide ubiquitous connectivity to the legacy and autonomous vehicles? This paper seeks to answer this question by combining recent leaps of innovation in network virtualization with remarkable feats of wireless communications. To do so, this paper proposes a novel paradigm called the Internet of autonomous vehicles (IoAV). We begin painting the picture of IoAV by discussing the salient features, and applications of IoAV which is followed by a detailed discussion on the key enabling technologies. Next, we describe the proposed layered architecture of IoAV and uncover some critical functions of each layer. This is followed by the performance evaluation of IoAV which shows the significant advantage of the proposed architecture in terms of transmission time and energy consumption. Finally, to best capture the benefits of IoAV, we enumerate some social and technological challenges and explain how some unresolved issues can disrupt the widespread use of autonomous vehicles in the future.

Which social decisions are intuitive? Which are deliberative? The dual-process approach to human sociality has emerged in the last decades as a vibrant and exciting area of research. Here, I review the existing literature on the cognitive basis of cooperation, altruism, honesty, equity-efficiency, positive and negative reciprocity, and moral judgments. For each of these domains, I list a number of open problems that I believe to be crucial to further advance our understanding of human social cognition. I conclude by making an attempt to introduce a game-theoretical framework to organize the existing empirical evidence. This framework seems promising, as it turns out to make predictions that are generally in line with the experimental data in all but one domain: positive reciprocity. I tried to keep the review self-contained, exhaustive, and research-oriented. My hope is that it can contribute to bring further attention to this fascinating area of research.

In last few years, the addiction of internet is apparently recognized as the serious threat to the health of society. This internet addiction gives an impetus to pornographic addiction because most of the pornographic content is accessible through internet. There have been ethical concerns on blocking the contents over internet. In India Uttarakhand High court has taken initiative for the blocking of pornographic content over internet. Technocrats are coming up with various innovative mechanisms to block the content over internet with various techniques, although long ago in 2015. The Supreme Court of India has already asked to block some of the websites but it could not be materialized. The focus of this research paper is to review the effectiveness of blocking existing web content blocking mechanism of pornographic websites in Indian context.