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Converging Technologies: A Critical Analysis of Cognitive Enhancement for Public Policy Application

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An Erratum to this article was published on 07 February 2015

Abstract

This paper investigates cognitive enhancement, specifically biological cognitive enhancement (BCE), as a converging technology, and its implications for public policy. With an increasing rate of technological advancements, the legal, social, and economic frameworks lag behind the scientific advancements that they support. This lag poses significant challenges for policymakers if it is not dealt with sufficiently within the right analytical context. Therefore, the driving question behind this paper is, “What contingencies inform the advancement of biological cognitive enhancement, and what would society look like under this set of assumptions?” The paper is divided into five components: (1) defining the current policy context for BCEs, (2) analyzing the current social and economic outcomes to BCEs, (3) investigating the context of cost-benefit arguments in relation to BCEs, (4) proposing an analytical model for evaluating contingencies for BCE development, and (5) evaluating a simulated policy, social, technological, and economic context given the contingencies. In order to manage the risk and uncertainty inherent in technological change, BCEs’ drivers must be scrutinized and evaluated.

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Notes

  1. For a more rigorous treatment of converging technologies, see European Parliament (2006), and Sandberg and Biostrome (2006).

  2. For example, see Drutman (2009) for a historical and empirical analysis on the pervasiveness of interest groups in BCE research.

  3. See Wolbring (2003) for an explanation of the medical model, namely the premise that medical challenges can be partition into neat cause-effect problems that can be cured and addressed.

  4. See Bostrom (2008a) and Bostrom (2009) for detailed discussions of costs and benefits

  5. See Taylor (2010) for a more detailed discussion of the relationship between industry and academia, in context of the drug industry.

  6. For example, see a recent news article Scotsman (2009) for relevant references and finding synopses.

  7. In this sense, not only does the literature not have an upper and lower bound on the magnitude of uncertainty, but it also does not have a fully developed understanding of the severity of the possibilities in between likely bounds.

  8. Next Big Future (2008).

  9. While this flow chart is necessarily simplified, we acknowledge that science-policy steps are non-linear and non-unidirectional. For purposes of this preliminary analysis, a visually simple and tractable model is presented.

  10. The author only found one known example: Lucke (2012).

  11. While a full discussion is outside the scope of the article, it is worthwhile to mention a current incompatibility between theological worldviews and BCEs. For example, nearly all world theologies view explicit cognitive modifications as an altering of spiritual essence. A normative stance is not taken in this article over the legitimacy to either side. However, because converging technology development is, arguably, inevitable, both sides need to address shared concerns in order to move forward together as a society. The ability for both sides to have these types of discussions will influence the rate and quality of technology policy governing BCEs.

  12. See http://www.interactivityfoundation.org/.

  13. It is noteworthy that this finding may not be wholly accurate; Greely (2010) reports another study finding that 34 % of students at a large public university had Adderall or Ritalin without prescriptions. Hence, use might be >20 %.

  14. This assumption is arguably valid because it is the most relevant policy option to investigate. For example, other alternatives, i.e. a backlash against BCEs, would pose a trivial policy evaluation defined by a simple default to the status quo.

  15. “Direct” and “indirect” effects denote the implications of BCEs, assuming a techno-optimistic future.

  16. See Makridis (2012) for an analysis of economic modeling techniques relating innovation and economic growth theory, and Block and Keller (2008) and Chesbrough (2003) for more historical accounts of innovation policy.

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Acknowledgments

Special thanks to Dr. Daniel Sarewitz, Dr. Michael Crow, and Kyle Whitman for their support, discussions, insight, and inspiration over science-policy and technological change.

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  1. Department of Engineering, Huang Engineering Center, Stanford University, 475 Via Ortega, Stanford, CA, 94305-4121, USA

    Christos Makridis

  2. North American Center for Transborder Study, Wilson Hall, 245 E Orange Mall, Third Floor, PO Box 877103, Tempe, AZ, 85287-7103, USA

    Christos Makridis

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Correspondence to Christos Makridis.

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An erratum to this article is available at http://dx.doi.org/10.1007/s11948-015-9630-8.

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Makridis, C. Converging Technologies: A Critical Analysis of Cognitive Enhancement for Public Policy Application. Sci Eng Ethics 19, 1017–1038 (2013). https://doi.org/10.1007/s11948-012-9396-1

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