Een Juridisch-Ethisch Kader voor Quantum Technologie →

Een bewerkte versie van deze bijdrage is gepubliceerd op platform VerderDenken.nl van het Centrum voor Postacademisch Juridisch Onderwijs (CPO) van de Radboud Universiteit Nijmegen. https://www.ru.nl/cpo/verderdenken/columns/we-nederland-voorbereiden-kwantumtoekomst/

Nederland moet zich voorbereiden op de toepassing van kwantumtechnologie, zegt jurist en Stanford Law School Fellow Mauritz Kop. Op het gebied van regulering, intellectueel eigendom en ethiek is er nog veel werk aan de winkel.

De Quantum Age roept veel juridische vragen op

Het gedrag van de natuur op de kleinste schaal kan vreemd en contra-intuïtief zijn. Hoe kunnen beleidsmakers de toepassingsgebieden van kwantumtechnologie, zoals quantum computing, quantum sensing en het quantum internet op een maatschappelijk verantwoorde manier reguleren? Dienen ethische kwesties een rol te spelen in regulering? De Quantum Age roept veel juridische vragen op.

Hoe kunnen we kwantumtechnologie reguleren?

Regulering van transformatieve technologie is een dynamisch, cyclisch proces dat de levensduur van de technologie en de toepassing volgt. Het vraagt om een flexibel wetgevend systeem dat zich snel kan aanpassen aan veranderende omstandigheden en maatschappelijke behoeften.

De eerste regelgevende stap om te komen tot een bruikbaar juridisch-ethisch kader is het koppelen van de Trustworthy AI-principes aan kwantumtechnologie. Die vullen we vervolgens aan met horizontale, overkoepelende regels die recht doen aan de unieke natuurkundige eigenschappen van quantum. Aan deze horizontale kernregels voegt de wetgever tenslotte verticale, industrie- of sectorspecifieke voorschriften toe. Die verticale voorschriften en gedragscodes zijn risk-based en houden rekening met de uiteenlopende behoeftes van economische sectoren waar het duurzame innovatiestimuli betreft. Zo ontstaat een gedifferentieerde, sectorspecifieke benadering aangaande incentives en risks.

Bewustwording van ethische, juridische en sociale aspecten

Een belangrijk onderdeel van het synchroniseren van onze normen, waarden, standaarden en principes met kwantumtechnologie is het creëren van bewustwording van de ethische, juridische en sociale aspecten ervan. De architectuur van systemen die zijn uitgerust met kwantumtechnologie moet waarden vertegenwoordigen die wij als samenleving belangrijk vinden.

Vooruitlopend op spectaculaire doorbraken in de toepassing van kwantumtechnologie is de tijd nu rijp voor regeringen, onderzoeksinstellingen en de markt om regulatoire en intellectuele eigendomsstrategieën voor te bereiden die passen bij de power van de technologie.

Nederland moet zich voorbereiden op een kwantumtoekomst, want die komt eraan.

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Regulating Transformative Technology in The Quantum Age: Intellectual Property, Standardization & Sustainable Innovation →

Stanford - Vienna Transatlantic Technology Law Forum, Transatlantic Antitrust and IPR Developments, Stanford University, Issue No. 2/2020 (Forthcoming)

New Stanford cutting edge tech law research: “Regulating Transformative Technology in The Quantum Age: Intellectual Property, Standardization & Sustainable Innovation”.

Quantum technology has many legal aspects

The behavior of nature at the smallest scale can be strange and counterintuitive. In addition to unique physical characteristics, quantum technology has many legal aspects. In this article, we first explain what quantum technology entails. Next, we discuss implementation and areas of application, including quantum computing, quantum sensing and the quantum internet. Through an interdisciplinary lens, we then focus on intellectual property (IP), standardization, ethical, legal & social aspects (ELSA) as well as horizontal & industry-specific regulation of this transformative technology.

The Quantum Age raises many legal questions

The Quantum Age raises many legal questions. For example, which existing legislation applies to quantum technology? What types of IP rights can be vested in the components of a scalable quantum computer? Are there sufficient market-set innovation incentives for the development and dissemination of quantum software and hardware structures? Or is there a need for open source ecosystems, enrichment of the public domain and even democratization of quantum technology? Should we create global quantum safety, security and interoperability standards and make them mandatory in each area of application? In what way can quantum technology enhance artificial intelligence (AI) that is legal, ethical and technically robust?

Regulating quantum computing, quantum sensing & the quantum internet

How can policy makers realize these objectives and regulate quantum computing, quantum sensing and the quantum internet in a socially responsible manner? Regulation that addresses risks in a proportional manner, whilst optimizing the benefits of this cutting edge technology? Without hindering sustainable innovation, including the apportionment of rights, responsibilities and duties of care? What are the effects of standardization and certification on innovation, intellectual property, competition and market-entrance of quantum-startups?

The article explores possible answers to these tantalizing questions.

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Machine Learning & EU Data Sharing Practices →

Stanford - Vienna Transatlantic Technology Law Forum, Transatlantic Antitrust and IPR Developments, Stanford University, Issue No. 1/2020

New multidisciplinary research article: ‘Machine Learning & EU Data Sharing Practices’.

In short, the article connects the dots between intellectual property (IP) on data, data ownership and data protection (GDPR and FFD), in an easy to understand manner. It also provides AI and Data policy and regulatory recommendations to the EU legislature.

As we all know, machine learning & data science can help accelerate many aspects of the development of drugs, antibody prophylaxis, serology tests and vaccines.

Supervised machine learning needs annotated training datasets

Data sharing is a prerequisite for a successful Transatlantic AI ecosystem. Hand-labelled, annotated training datasets (corpora) are a sine qua non for supervised machine learning. But what about intellectual property (IP) and data protection?

Data that represent IP subject matter are protected by IP rights. Unlicensed (or uncleared) use of machine learning input data potentially results in an avalanche of copyright (reproduction right) and database right (extraction right) infringements. The article offers three solutions that address the input (training) data copyright clearance problem and create breathing room for AI developers.

The article contends that introducing an absolute data property right or a (neighbouring) data producer right for augmented machine learning training corpora or other classes of data is not opportune.

Legal reform and data-driven economy

In an era of exponential innovation, it is urgent and opportune that both the TSD, the CDSM and the DD shall be reformed by the EU Commission with the data-driven economy in mind.

Freedom of expression and information, public domain, competition law

Implementing a sui generis system of protection for AI-generated Creations & Inventions is -in most industrial sectors- not necessary since machines do not need incentives to create or invent. Where incentives are needed, IP alternatives exist. Autonomously generated non-personal data should fall into the public domain. The article argues that strengthening and articulation of competition law is more opportune than extending IP rights.

Data protection and privacy

More and more datasets consist of both personal and non-personal machine generated data. Both the General Data Protection Regulation (GDPR) and the Regulation on the free flow of non-personal data (FFD) apply to these ‘mixed datasets’.

Besides the legal dimensions, the article describes the technical dimensions of data in machine learning and federated learning.

Modalities of future AI-regulation

Society should actively shape technology for good. The alternative is that other societies, with different social norms and democratic standards, impose their values on us through the design of their technology. With built-in public values, including Privacy by Design that safeguards data protection, data security and data access rights, the federated learning model is consistent with Human-Centered AI and the European Trustworthy AI paradigm.

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