Auditing the Impact of Neuro-Advancements on Health Equity

Gregor Wolbring

Abstract


Health equity understood as the ability to live a healthy life, to have a good life, is impacted by many social determinants and by the social marginalization of various groups. “Measures” that use indicators to cover social determinants of a good life are useful tools to audit the impact of neuro-advancements on health equity. In this scoping review, I covered over 50 neurotechnologies, neuroenhancement, artificial intelligence (AI) machine learning (ML), robotics, neuroethics, neuro-governance and neurotechnology governance and various “measures” that focus on the ability to have a good life to answer three research questions: 1) Are the “measures” engaged with in the academic literature covering health equity or the chosen technologies? 2) Does the academic literature focusing on the technologies covered, neuroethics, or neurotechnology governance engage with health equity? 3) To what extent does the academic literature focusing on the technologies covered engage with the different primary and secondary indicators of four of the “measures” (social determinants of health, Better Life Index, Canadian Index of Well-Being, and community-based rehabilitation matrix)? For the scoping review, I examined the academic literature present in SCOPUS, which includes all Medline articles, and the 70 databases accessible under EBSCO-HOST and I employed a quantitative hit count approach for the analysis. I found that the term “health equity” was only mentioned in conjunction with the terms “determinants of health” and “social determinants of health” in a substantial way. Three of the terms linked to the “measures” were each mentioned in less than 10 abstracts and 16 terms linked to the “measures” were not mentioned at all in conjunction with the term “health equity”. Health equity was also rarely to not at all mentioned in conjunction with the different technologies covered and not at all in conjunction with the terms “neuroethics”, “neurotechnology governance” or “neuro-governance”. Finally, there was uneven engagement with the primary and secondary indicators of the four chosen “measures” in conjunction with the technologies covered. The results reveal vast opportunities at the intersections of neuroethics and neuro-governance and science and technology governance in general, health equity, social justice, and wellbeing discourses.




J Neurol Res. 2021;000(000):000-000
doi: https://doi.org/10.14740/jnr695

Keywords


Health equity; Robotics; Artificial intelligence; Machine learning; Neurotechnology; Neuroenhancement; Neuroethics; Well-being measures

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