One of the hallmarks of human existence is our ability to be creative and to express ourselves through art. In an opinion piece for WebProNews, the novelist and technology writer Jason Lee Miller stated:
«Chess is one thing, but if we get to the point computers can best humans in the arts – those splendid, millennia-old expressions of the heart and soul of human existence – then why bother existing?»
2.1.
Auto-generated patent applications ^
As we saw above, one of the success stories of creative AI was the emergence of automated text generation. While traditionally seen as a problem for copyright law, these approaches become relevant for patent law when patent specifications are used as input. Cloem is an example of such a system.8 The algorithm produces a large number of permutations of a seed claim by rearranging phrases and substituting terms with alternative definitions, synonyms or antonyms. Cloem asserts that its algorithm is not merely random; rather, it applies patent drafting best practices to produce alternative claims. Crucially, the resulting claims are not necessarily meaning-preserving variants of the original, which would mean no «new» invention was made, just a new description of an old invention generated. Rather, they potentially enlarge the original invention’s scope, or particularly in the case of substitution with antonyms, describe a distinct and new invention. These variant claims are time-stamped and optionally published online using persistent webpages. Similarly, the art project AllPriorArt.com and its sister site AllTheClaims.com use a technology that autonomously generates patent claims and descriptions. This computer system parses and randomly reassembles texts from patents and published applications from the US patent database to generate patent texts describing possible new inventions. The texts are time-stamped and published online on AllPriorArt’s website.
2.2.
Genetic programming and algorithmic discovery ^
3.
Patentability of Computer-Assisted Inventions ^
Creativity and inventiveness require more than novelty, however.34 Recall that the patentability requirement of an inventive step demands that an invention «is not obvious to the person skilled in the art, having regard to any matter which forms part of the state of the art.»35 Granting monopolies over obvious inventions would contribute little to society and prevent others from engaging in technological modifications and ordinary progresses.36 Given the ability of computers to supplant human intuition with brute force computational power, the notional skilled person and the bar for obviousness may need to be reinterpreted in light of AI in order for the inventive step requirement to serve its intended purpose.37
Assessing the existence of an inventive step concludes with determining whether «the differences between the inventive concept and the prior art constitute steps which would have been obvious to the person skilled in the art.» What will be considered obvious, and therefore non-patentable, must reflect changing inventive practices; for example, an invention that on its surface may seem inventive, may in fact be the obvious output of a computer programmed to generate inventions «like hot water from a kettle.»38 This in some ways mirrors Searle’s Chinese room argument: Just as we should assess the «ability to speak Chinese» from the inside perspective, not just the end result, we may have to separate for purpose of the inventive step assessment an internal perspective made in knowledge of everything that was involved in generating the idea from an outside perspective that looks at the result only. An invention that results from a computer performing a large number of trivial calculations or brute force trial-and-error testing may seem non-obvious on its face because it had not been foreseen; however, the invention may be seen as obvious because of the inevitability of discovery as anyone having ordinary skill using one of the above-described AI algorithms could have produced the same result.39
4.
Beyond IP: The self-made machine ^
In the past, arguments that called for a radical re-think of the legal status of robotic devices and how to attribute liability to them focussed on the partial unpredictability of their behaviour. Autonomy, so the argument, breaches the causal nexus and creates as a result a responsibility gap.40 The recent EU motion on the regulation of robotics took this idea as a starting point to push the idea of robots as holder of legal rights further than this has been done before outside highly speculative academic papers.41 One idea mooted in the consultation is the idea that every robot of a to-be-specified autonomy and sophistication could be associated with a unique fund, similar to the old notion of peculium from the Roman law of slavery.42 This money would not be controlled by owner or manufacturer of the machine and could (in part) be payment to the robot for work done. Its role would be to cover liabilities for harm inflicted by the robot to third parties similar to an insurance scheme. More radically, the proposal also suggests that it could be used as a way to compensate society for more generic harm caused by automation such as technological unemployment, similar to an income tax. The EU motion also states that they do not foresee major conceptual changes in the field of IP law.
- 1 Work on this paper was supported by CREATE, the RCUK Centre for Copyright in the Creative Economy.
- 2 Boden, Creativity and artificial intelligence, Art Int. 1998, Issue 103(1), pp. 347–356; for recent discussions see e.g. Veale, Exploding the Creativity Myth: The Computational Foundations of Linguistic Creativity, Bloomsbury, London, 2012 or McCormack/d’Inverno (eds.), Computers and Creativity, Springer, Berlin 2012.
- 3 Haupenthal, Geschichte der Würfelmusik in Beispielen, Dissertation, Univ. Saarbrücken, Saarbrücken 1994.
- 4 KAC, Foundation and development of robotic art, Art Journal 1994, Issue 56.3, pp. 60–67.
- 5 See Burnham, Robot and Cyborg Art, in: Burnham (ed.), Beyond Modern Sculpture, George Braziller New York 1968, pp. 68–77.
- 6 See e.g. Wright, Algorithmic authors, Communications of the ACM 2015, Issue 58/11, pp. 12–14.
- 7 Allen et al., StatsMonkey: A Data-Driven Sports Narrative Writer. Proc AAAI Fall Symposium: Computational Models of Narrative, New York, ACM 2010.
- 8 See https://www.cloem.com/flat/technology/ (all Websites accessed on 20 January 2017); Cloem, Untitled statement on AllPriorArt (2016) available at https://www.facebook.com/cloempatent/posts/1689691667956972; an example of Cloem-generate claims can be found at https://www.cloem.com/media/pdf/T56231165.pdf.
- 9 For the UK see e.g. Patents Act 1977, sections 2(1), 3.
- 10 SmithKline Beecham Plc’s (Paroxetine Methanesulfonate), Patent [2006] RPC 10; General Tire & Rubber Company v Firestone Tyre & Rubber Company Limited, [1972] RPC 457, at 485–486.
- 11 Patents Act 1977, section. 3.
- 12 Hattenbach/Glucoft, Patents In An Era Of Infinite Monkeys And Artificial Intelligence, Stan Tech L Rev 2015, pp. 3232–3251, at 3240; In re: Winslow, 365 F2d 1017, 1020 (CCPA 1965).
- 13 Patents Act 1977, section 2(2); see also Convention on the Grant of European Patents (European Patent Convention), section 54(2): «Everything made available to the public by means of a written or oral description, by use, or in any other way, before the date of filing of the European patent application.»
- 14 European Patent Office, «Guidelines for Examination», sections 7.5, 7.5.1, available at http://www.epo.org/law-practice/legal-texts/html/guidelines/e/index.htm; Unwired Planet International Ltd v Huawei Technologies Co Ltd & Ors [2015] EWHC 3366 (Pat).
- 15 Waelde et al, Contemporary Intellectual Property: Law and Policy, OUP, Oxford 2014, at 11.82; Bristol-Myers Co’s Application, [1969] RPC 146 T 1553/06.
- 16 Waelde (note 15), at 11.83; H Lundbeck A/S v Norpharma SpA, [2011] EWHC 907 (Pat).
- 17 H Lundbeck A/S v Norpharma SpA, [2011] EWHC 907 (Pat).
- 18 Searle, Minds, brains, and programs, Behavioral and Brain Sciences 1980, Issue 3 (3), pp. 417–457.
- 19 Sacha/Varona, Artificial intelligence in nanotechnology, 24 Nanotechnology 2013, pp. 1–13, at 1, available at: http://iopscience.iop.org/article/10.1088/0957-4484/24/45/452002/meta.
- 20 Nosengo, Can artificial intelligence create the next wonder material?, Nature 2016, Issue 533, pp. 22–25; Abbot, I Think, Therefore I Invent, BCL Rev 2016, Issue 53, pp. 1079–1125.
- 21 See e.g. Koza, Genetic programming: on the programming of computers by means of natural selection Vol 1, MIT Press, Boston 1992.
- 22 Poli/Koza, Genetic Programming, in: Burke/Kendall (eds.), Search Methodologies: Introductory Tutorials in Optimization and Decision Support Techniques, Springer, Berlin 2014, pp. 145–147.
- 23 Koza, Human-Competitive Results Produced by Genetic Programming, Genet Program Evol. 2010, Issue 11, pp. 251– 284, at 265; Koza et al., Evolving Inventions, Scientific American 2003, pp. 52–59, at 52; Keane/Koza/Streeter, Apparatus for improved general-purpose PID and non-PID controllers, US Patent No US6847851 (B1).
- 24 Koza (note 23), at 265.
- 25 Hornby/Lohn/Inden, Computer-Automated Evolution of an X-Band Antenna for NASA’s Space Technology 5 Mission, Evol Comput 2006, Issue 19, pp. 1–23, at 2.
- 26 Lohn/Hornby/Linden, An Evolved Antenna For Deployment On NASA’s Space Technology 5 Mission, in: U. O’Reilly et al. (eds.), Genetic Programming Theory and Practice II, SSBM, Cambridge 2005, pp. 301–315, at 311.
- 27 King, Functional genomic hypothesis generation and experimentation by a robot scientist, Nature 2004, Issue 427, pp. 247–252, at 247, 251.
- 28 King (note 27), at 47.
- 29 Blunchen, Robot Makes Scientific Discovery All by Itself, Wired 2009, available at: http://www.wired.com/2009/04/robotscientist/.
- 30 Williams et al., Cheaper faster drug development validated by the repositioning of drugs against neglected tropical diseases, J R Soc Interface 2015, Issue 12, p. 20141289.
- 31 Hattenbach/Glucoft (note 12), p. 44; Abbot, Hal the Inventor: Big Data and Its Use by Artificial Intelligence, in: Hamid Ekbia et al. (eds.), Big Data Is Not a Monolith, MIT Press, Cambridge 2016, available at: http://ssrn.com/abstract=2565950, at 12.
- 32 35 USC §103(a).
- 33 Vertinsky/Rice, Thinking About Thinking Machines: Implications Of Machine Inventors For Patent Law, BU J Sci & Tech L 2002, Issue 8, pp. 574–613 at 576.
- 34 Bundy, What is the difference between true creativity and novelty, Behav Brain Sci 1994, Issue 17, p. 533–534.
- 35 Patents Act 1977, section 3.
- 36 WIPO Standing Committee on the Law of Patents, «Study on Inventive Step» (2015), available at: http://www.wipo.int/edocs/mdocs/scp/en/scp_22/scp_22_presentation_inventive_step.pdf.
- 37 Vertinsky/Rice (note 33), p. 39; Plotkin, The Genie in the Machine: How Computer-Automated Inventing is Revolutionizing Law & Business, SUP, Stanford 2009, p. 102.
- 38 Vertinsky/Rice (note 33), p. 595.
- 39 Vertinsky/Rice (note 33), p. 596; Plotkin (note 37), p. 108.
- 40 Matthias, Automaten als Träger von Rechten, Logos Verlag, Berlin 2010; Beck, The problem of ascribing legal responsibility in the case of robotics, AI & Society 2016, Issue 4, pp. 473–481.
- 41 Committee on Legal Affairs, Draft report with recommendations to the Commission on Civil Law Rules on Robotics (2015/2103(INL)), 31 May 2016, available at: http://www.europarl.europa.eu/sides/getDoc.do?pubRef=-//EP//NONSGML%2BCOMPARL%2BPE-582.443%2B01%2BDOC%2BPDF%2BV0//EN.
- 42 Pagallo, Killers, fridges, and slaves: a legal journey in robotics, AI & Society 2011, Issue 26, pp. 347–354.
- 43 For an application to IP see Justin, The Philosophy of Intellectual Property, Geo. LJ 1988, Issue 77, pp. 287–366.
- 44 EU Motion 2016, at p. 31 f.