The moral authority of ethics codes stems from an assumption that they serve a unified society, yet this ignores the political aspects of any shared resource. The sociologist Howard S. Becker challenged researchers to clarify their power and responsibility in the classic essay: Whose Side Are We On. Building on Becker's hierarchy of credibility, we report on a critical discourse analysis of data ethics codes and emerging conceptualizations of beneficence, or the "social good", of data technology. The analysis revealed that ethics codes from corporations and professional associations conflated consumers with society and were largely silent on agency. Interviews with community organizers about social change in the digital era supplement the analysis, surfacing the limits of technical solutions to concerns of marginalized communities. Given evidence that highlights the gulf between the documents and lived experiences, we argue that ethics codes that elevate consumers may simultaneously subordinate the needs of vulnerable populations. Understanding contested digital resources is central to the emerging field of public interest technology. We introduce the concept of digital differential vulnerability to explain disproportionate exposures to harm within data technology and suggest recommendations for future ethics codes.
However, in recent years symbolic AI has been complemented and sometimes replaced by (Deep) Neural Networks and Machine Learning (ML) techniques. This has vastly increased its potential utility and impact on society, with the consequence that the ethical debate has gone mainstream. Such a debate has primarily focused on principles--the'what' of AI ethics (beneficence, non-maleficence, autonomy, justice and explicability)--rather than on practices, the'how.' Awareness of the potential issues is increasing at a fast rate, but the AI community's ability to take action to mitigate the associated risks is still at its infancy. Therefore, our intention in presenting this research is to contribute to closing the gap between principles and practices by constructing a typology that may help practically-minded developers'apply ethics' at each stage of the pipeline, and to signal to researchers where further work is needed. The focus is exclusively on Machine Learning, but it is hoped that the results of this research may be easily applicable to other branches of AI. The article outlines the research method for creating this typology, the initial findings, and provides a summary of future research needs.
Artificial intelligence (AI) is a technology which is increasingly being utilised in society and the economy worldwide, and its implementation is planned to become more prevalent in coming years. AI is increasingly being embedded in our lives, supplementing our pervasive use of digital technologies. But this is being accompanied by disquiet over problematic and dangerous implementations of AI, or indeed, even AI itself deciding to do dangerous and problematic actions, especially in fields such as the military, medicine and criminal justice. These developments have led to concerns about whether and how AI systems adhere, and will adhere to ethical standards. These concerns have stimulated a global conversation on AI ethics, and have resulted in various actors from different countries and sectors issuing ethics and governance initiatives and guidelines for AI. Such developments form the basis for our research in this report, combining our international and interdisciplinary expertise to give an insight into what is happening in Australia, China, Europe, India and the US.
It is very important to adhere strictly to ethical and social influences when delivering most of our life to artificial intelligence systems. With industry 4.0, the internet of things, data analysis and automation have begun to be of great importance in our lives. With the Yapanese version of Industry 5.0, it has come to our attention that machine-human interaction and human intelligence are working in harmony with the cognitive computer. In this context, robots working on artificial intelligence algorithms co-ordinated with the development of technology have begun to enter our lives. But the consequences of the recent complaints of the Robots have been that important issues have arisen about how to be followed in terms of intellectual property and ethics. Although there are no laws regulating robots in our country at present, laws on robot ethics and rights abroad have entered into force. This means that it is important that we organize the necessary arrangements in the way that robots and artificial intelligence are so important in the new world order. In this study, it was aimed to examine the existing rules of machine and robot ethics and to set an example for the arrangements to be made in our country, and various discussions were given in this context.
One of the undisputable realities of moving into a digital work era is the continuous improvement in technologies which mimic and replicate what human employees are doing. The introduction of'bots' into the workplace to perform logic-based and repetitive tasks is becoming a common occurrence. These task robots are able to perform activities faster, with greater accuracy and more efficiently that their human colleagues. In fact their capacity is close to 700 per cent greater than the human employee, who generally works at a 60 per cent utilisation rate for 7-8 hours a day, can be absent for a variety of reasons, doesn't work 7 days a week, and who's productivity is influenced by a plethora of human frailties. It's no wonder'bots' are attractive to organisations for this type of work.