Governance and Assessment of Future Spaces: A Discussion of Some Issues Raised by the Possibilities of Human-Machine Mergers

‘In faith, I do not love thee with mine eyes, For they in thee a thousand errors note; But ‘tis my heart that loves what they despise …’ 1 This sonnet and the ancient Japanese notion of wabi-sabi view aesthetics or beauty as imperfect, impermanent and incomplete. Rather than celebrating the human diversity created by our ‘imperfections’, today's society increasingly focuses on them as ‘areas for improvement’, often via a doctor’s scalpel or the latest gadget. Developments in science, technology, engineering, mathematics and medicine (STEMM) promise a tomorrow where ‘errors’ or ‘deficiencies’ in an organism’s genetic and/or phenotypic makeup can be modulated, enhanced, corrected, redefined or eradicated by, for instance, networks of biological nanomachines. Upgraded organisms will be convolutions of organic parts, electronic components, microchips, and biomechanotronic devices. Humans 1.0, Humans 2.0 and transhumans will live in new fully immersive worlds (virtual reality), inhabit a modified real world (augmented reality), and exist with an altered body schema (mixed-reality). This future world could be a place of total technological convergence, where it may not be possible to ensure privacy of an individual’s thoughts. It could also be a place where people can be subjected to Social Engineering and manipulation, including the potential for viruses and malware infecting the brain or body, as well as new forms of external control of individuals by third parties. In this discussion paper, we will explore the potential privacy, security, and ethical issues raised by humanmachine mergers. The focus is on research, development and products at the intersection of robotics, artificial intelligence, Big Data, and smart computing. We suggest that there is a need for a more holistic approach to the assessment of technology and its governance. Additionally, we suggest that in order to determine how the law will need to respond to this particular future space, it is necessary to understand the full impacts of human-machine mergers on societies and our planet – to go beyond these three issues. Since STEMM-related activities are promising a cornucopia of future spaces, we will propose that the problems of governance and assessment require a new conception of ‘responsible research and innovation’, one that is fulfilled by our recently proposed FLE5 SH framework.2 To some extent the FLE5 SH framework can be seen as allowing the formation of a social contract, whereby all stakeholders are required to engage in a review of this wider spectrum of the possible impacts of technologies. We suggest that a Precautionary Principle approach may be of assistance in considering the impacts of technologies, remembering that especially in the context of software based systems, it is always useful to think first and bugfix later

Buying your genetic self online: Pitfalls and potential reforms in DNA testing

Today's orld is one of constant monitoring and tracking-sometimes driven by us, sometimes driven by others. Developments in the field of health and identity are no exception. New technologies, such as wearable devices, and other technologies in consumer-centered health care allow us to track our fitness and health data, and they connect us with others

Protecting the rights of consumers - clickwrap contracts and direct-to-consumer genetic testing

This thesis examines the regulation of the direct-to-consumer genetic testing industry through analysis of the industryâs use of wrap contracts (clickwrap and browsewrap), A significant portion of the thesis consists of a comparative document review of the publicly available wrap contracts of DTCGT companies provided tests for health purposes. It also considers other regulatory responses to date. Due to the lack of industry specific regulation it argues that the use of wrap contracts can be viewed as a means of industry self-regulation and a form of private legislation. This means that governance is skewed heavily in favour of companies and it creates an imbalance in the respective rights and obligations of the parties â company and consumer â which is likely to result in consumer detriment. It is argued that certain types of terms commonly include in DTCGT contracts, including: unilateral variation clauses; some exclusion clauses; choice of law clauses; indemnity; and consent clauses are likely to be deemed unfair and unenforceable under UK law. It recommends that in the short-term the Competition and Markets Authority should undertake a compliance review of DTCGT contracts in order to improving contracts for consumers. In the long term, companies should also be complying with data protection law, as well as legislation on medical devices and the provisions of the Human Tissue Act and there may be a need for industry specific legislation

The age of personalized medicine—From patients to consumers: The digital environment, clickwrap contracts, and implications for autonomy

How many online contracts have you entered into this year and how many of those did you actually read? This chapter explores the impact that the designed environment of websites and electronic contracts have on the exercise of individual autonomy in the context of the example of direct-to-consumer genetic tests (DTC). DTC tests for health purposes can be viewed as an example of Personalized Medicine, but as the mode of sale usually lacks the involvement of a physician or genetic counsellor and the industry is largely unregulated, companies often rely on their contracts and privacy policies to govern relationships with consumers. This chapter seeks to shed light on the impact that offering these services online and relying on electronic contracts, which people have grown accustomed to ignoring, has on the exercise of autonomy and an individual’s ability to make an informed choice in this context

‘Only a click away — DTC genetics for ancestry, health, love…and more: A view of the business and regulatory landscape’

I provide an overview of the current state of the direct-to-consumer (DTC) genetic testing industry and the challenges that different types of testing pose for regulation. I consider the variety of services currently available. These range from health and ancestry tests to those for child talent, paternity, and infidelity. In light of the increasingly blurred lines among different categories of testing, I call for a broader discussion of DTC governance. I stress the importance of shifting our attention from the activities of the most prominent companies to viewing DTC genetics as an industry with a wide spectrum of services and raising a wide variety of issues. These issues go beyond questions of clinical utility and validity to those of data security, personal identity, race, and the nature of the family. Robust DTC testing has the power to provide meaningful clinical, genealogical and even forensic information to those who want it; in unscrupulous hands, however, it also has the power to deceive and exploit. I consider approaches to help ensure the former and minimize the latter

Essentials of a robust deep learning system for diabetic retinopathy screening: A systematic literature review

This systematic review was performed to identify the specifics of an optimal diabetic retinopathy deep learning algorithm, by identifying the best exemplar research studies of the field, whilst highlighting potential barriers to clinical implementation of such an algorithm. Searching five electronic databases (Embase, MEDLINE, Scopus, PubMed, and the Cochrane Library) returned 747 unique records on 20 December 2019. Predetermined inclusion and exclusion criteria were applied to the search results, resulting in 15 highest-quality publications. A manual search through the reference lists of relevant review articles found from the database search was conducted, yielding no additional records. A validation dataset of the trained deep learning algorithms was used for creating a set of optimal properties for an ideal diabetic retinopathy classification algorithm. Potential limitations to the clinical implementation of such systems were identified as lack of generalizability, limited screening scope, and data sovereignty issues. It is concluded that deep learning algorithms in the context of diabetic retinopathy screening have reported impressive results. Despite this, the potential sources of limitations in such systems must be evaluated carefully. An ideal deep learning algorithm should be clinic-, clinician-, and camera-agnostic; complying with the local regulation for data sovereignty, storage, privacy, and reporting; whilst requiring minimum human input

Setting of an Observatory of clinical trial transition regarding data sharing; IMPACT Observatory

Methodology of the IMProving Access to Clinical Trial data -IMPACT Observatory: development of network -working group; literature; surveys, interviews, repositories<br