Reassessing values for emerging big data technologies: integrating design-based and application-based approaches

Abstract

Through the exponential growth in digital devices and computational capabilities, big data technologies are putting pressure upon the boundaries of what can or cannot be considered acceptable from an ethical perspective. Much of the literature on ethical issues related to big data and big data technologies focuses on separate values such as privacy, human dignity, justice or autonomy. More holistic approaches, allowing a more comprehensive view and better balancing of values, usually focus on either a design-based approach, in which it is tried to implement values into the design of new technologies, or an application-based approach, in which it is tried to address the ways in which new technologies are used. Some integrated approaches do exist, but typically are more general in nature. This offers a broad scope of application, but may not always be tailored to the specific nature of big data related ethical issues. In this paper we distil a comprehensive set of ethical values from existing design-based and application-based ethical approaches for new technologies and further focus these values to the context of emerging big data technologies. A total of four value lists (from techno-moral values, value-sensitive design, anticipatory emerging technology ethics and biomedical ethics) were selected for this. The integrated list consists of a total of ten values: human welfare, autonomy, non-maleficence, justice, accountability, trustworthiness, privacy, dignity, solidarity and environmental welfare. Together, this set of values provides a comprehensive and in-depth overview of the values that are to be taken into account for emerging big data technologies.

From What to How: An Initial Review of Publicly Available AI Ethics Tools, Methods and Research to Translate Principles into Practices

“…This approach is also used in the disciplinary ethical guidance produce for internet-mediated researchers by the Belmont Report (Anabo et al 2019 ), and by La Fors et al ( 2019 ) who sought to integrate existing design-based ethical approaches for new technologies by matching lists of values the practical abstraction from mid-level ethics (principles) to what (Hagendorff 2019 ) calls ‘microethics.’ This translation is a process that gradually reduces the indeterminacy of abstract norms to produce desiderata for a ‘minimum-viable-ethical-(ML)product’ (MVEP) that can be used by people who have various disciplinary backgrounds, interests and priorities (Jacobs and Huldtgren 2018 ). The outcome of this translation process is shown in Table 5 .…”

“…The second limitation is related to the design of the typology itself. As (La Fors et al 2019 ) attest, the “neat theoretical distinction between different stages of technological innovation does not always exist in practice, especially not in the development of big data technologies.” This implies that by categorising the tools by stage of development, we might be reducing their usability as developers in different contexts might follow a different pattern or feel as though it is ‘too late’ to, for example, engage in stakeholder engagement if they have reached the ‘build’ phase of their project, whereas the reality it is never too late.…”

Value-Oriented and Ethical Technology Engineering in Industry 5.0: A Human-Centric Perspective for the Design of the Factory of the Future

“…Instead, the values listed in anticipatory emerging technology ethics are the following: harms and risks, rights and freedoms, autonomy, human dignity, privacy, property, animal rights and animal welfare, (distributive) justice, and well-being and the common good. The recent interest towards the implementation of values into emerging technologies, such as Big Data, find application in [63], that distilled a comprehensive set of 10 ethical values for new technologies: human welfare, autonomy, non-maleficence, justice, accountability, trustworthiness, privacy, dignity, solidarity, and environmental welfare. VSD studies also have provided various lists of human values that may be important to technologies design, they typically include values such as: Welfare, Ownership and Property, Privacy, Freedom from Bias, Universal Usability, Trust, Autonomy, Informed Consent, Accountability, Courtesy, Identity, Calmness and Environmental Sustainability among others.…”

Viés algorítmico – um balanço provisório

“…Um segundo aspecto interessante é que boa parte da literatura jurídica busca apresentar e categorizar o fenômeno e suas consequências, além de explorar possíveis soluções normativas sistêmicas, como maior transparência, auditabilidade, responsabilização (accountability) etc. (AYRE; CRANER, 2018; BAROCAS; SELBST, 2016;MAYSON, 2018;LA FORS;CUSTERS;KEYMOLEN, 2019;DIAKOPOULOS, 2016). Diakopoulos (2016), por exemplo, propõe pensar accountability e transparência com base na divulgação de informações sobre intenções e envolvimento humanos, qualidade dos dados e do modelo, quais as especificidades das inferências realizadas pelo algoritmo, e como e para o que o algoritmo é mobilizado (denominado por ele "presença algorítmica").…”