Innovation, Technology & Law

Blog over Kunstmatige Intelligentie, Quantum, Deep Learning, Blockchain en Big Data Law

Blog over juridische, sociale, ethische en policy aspecten van Kunstmatige Intelligentie, Quantum Computing, Sensing & Communication, Augmented Reality en Robotica, Big Data Wetgeving en Machine Learning Regelgeving. Kennisartikelen inzake de EU AI Act, de Data Governance Act, cloud computing, algoritmes, privacy, virtual reality, blockchain, robotlaw, smart contracts, informatierecht, ICT contracten, online platforms, apps en tools. Europese regels, auteursrecht, chipsrecht, databankrechten en juridische diensten AI recht.

Berichten met de tag regulation
Quantum ELSPI: Ethical, Legal, Social and Policy Implications of Quantum Technology

Call for Papers Quantum ELSPI

Delighted to announce that the Quantum ELSPI call for papers is now open! AIRecht Director & Stanford Law School TTLF Fellow Mauritz Kop has the honor to guest-edit a Topical Collection for Digital Society, a new journal edited by Luciano Floridi (Oxford Internet Institute). This project is a Stanford/Oxford collaboration that aims to explore uncharted territories of Ethical, Legal, Social and Policy Implications of Quantum Technology. Articles should be submitted before 15 February 2022 and will be double blind peer reviewed. Accepted articles will be published by Springer Nature.

You can find the Quantum ELSPI collection page here: https://link.springer.com/collections/eiebhdhagd.

Download the Springer Nature Quantum-ELSPI Call for Papers here: TC_Quantum ELSPI_Call for papers

ELSPI stratagems for quantum technology

Anticipating spectacular advancements in real-world quantum driven products and services, the time is ripe for governments, academia and the market to prepare regulatory and business strategies that balance their societal impact. This topical collection seeks to provide informed suggestions on how to maximize benefits and mitigate risks of applied quantum technology. It intends to deliver insights and actionable recommendations on how and when to address identified opportunities and challenges, which can then be refined into plausible, evidence-based policy decisions by stakeholders across the world.

Special edition of Digital Society

In this special edition of Digital Society, we aim for scholars to reflect on the multifaceted questions associated with Quantum ELSPI. In addition to learning from history and connecting quantum to other big picture trends, quantum should be treated as something completely unique and unprecedented. We especially welcome cross-disciplinary contributions that look beyond research silos and integrate law, economic theory, ethics, sociology, philosophy of science, quantum information science, and sustainable innovation policy, and that consider how to improve ELSPI stratagems for quantum technology. We encourage authors to be pioneers in this complex, and at times counterintuitive field.

Multifaceted questions associated with Quantum ELSPI

Questions and topics that could be addressed by contributions in the topical collection are not restricted to, but could include the following:

-Potential strategies for industries facing disruption such as the cybersecurity industry and financial institutions. What role could antitrust law, intellectual property, prizes, fines, funding, taxes, lifelong learning and labor mobility play while incentivizing innovation?

-How should dual use applications be managed? How do we balance freedom with control? What role could a Quantum Treaty play to make our world a safer place?

-The creation of a list of quantum-specific themes, goals, benefits and risks that need to be addressed by universal, overarching principles of responsible quantum design and application, including a definition of hi-risk quantum-systems.

-How can policy makers learn from history and adjacent fields - such as AI, biotechnology, nanotechnology, semiconductors and nuclear - when regulating exponential innovation and ensuring equal access to quantum computing, sensing and the quantum internet? How can winner take all effects and a quantum divide be prevented? To what extent does governing digitization driven by classical computing paradigms (binary digits) differ from governing quantum computing (qubits)?

-It is not inconceivable that the development and uptake of transnational quantum principles will run along the lines of democratic and authoritarian tech governance models. Against that background, how can we embed cultural norms, liberal values, democratic principles, human rights and fundamental freedoms in globally accepted interoperability standards?

-How can we implement ethically aligned design into our quantum systems architecture and infrastructure? How can quantum technology impact assessments help achieve these goals?

Guest-Editor Quantum ELSPI: Mauritz Kop (Stanford Law School, Stanford University)

Editor-in-Chief Digital Society: Luciano Floridi (Oxford Internet Institute, Oxford University)

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Establishing a Legal-Ethical Framework for Quantum Technology

Yale Law School, Yale Journal of Law & Technology (YJoLT) The Record 2021

New peer reviewed cross-disciplinary Stanford University Quantum & Law research article: “Establishing a Legal-Ethical Framework for Quantum Technology”.

By Mauritz Kop

Citation: Kop, Mauritz, Establishing a Legal-Ethical Framework for Quantum Technology (March 2, 2021). Yale J.L. & Tech. The Record 2021, https://yjolt.org/blog/establishing-legal-ethical-framework-quantum-technology

Download the article here: Kop_Legal-Ethical Framework for Quantum Tech-Yale

Please find a short abstract below:

What is quantum technology?

Quantum technology is founded on general principles of quantum mechanics and combines the counterintuitive physics of the very small with engineering. Particles and energy at the smallest scale do not follow the same rules as the objects we can detect around us in our everyday lives. The general principles, or properties, of quantum mechanics are superposition, entanglement, and tunnelling. Quantum mechanics aims to clarify the relationship between matter and energy, and it describes the building blocks of atoms at the subatomic level.

Raising Quantum Awareness

Quantum technologies are rapidly evolving from hypothetical ideas to commercial realities. As the world prepares for these tangible applications, the quantum community issued an urgent call for action to design solutions that can balance their transformational impact. An important first step to encourage the debate is raising quantum awareness. We have to put controls in place that address identified risks and incentivise sustainable innovation.

Connecting AI and Nanotechnology to Quantum

Establishing a culturally sensitive legal-ethical framework for applied quantum technologies can help to accomplish these goals. This framework can be built on existing rules and requirements for AI. We can enrich this framework further by integrating ethical, legal and social issues (ELSI) associated with nanotechnology. In addition, the unique physical characteristics of quantum mechanics demand universal guiding principles of responsible, human-centered quantum technology. To this end, the article proposes ten guiding principles for the development and application of quantum technology.

Risk-based Quantum Technology Impact Assessment Tools

Lastly, how can we monitor and validate that real world quantum tech-driven implementations remain legal, ethical, social and technically robust during their life cycle? Developing concrete tools that address these challenges might be the answer. Raising quantum awareness can be accomplished by discussing a legal-ethical framework and by utilizing risk-based technology impact assessment tools in the form of best practices and moral guides.

Mauritz Kop is a Stanford Law School TTLF Fellow, Founder of MusicaJuridica and strategic intellectual property lawyer at AIRecht, a leading 4th Industrial Revolution technology consultancy firm based in Amsterdam, The Netherlands. The author is grateful to Mark Brongersma (Department of Materials Science and Engineering at Stanford University), Mark Lemley (Stanford Law School), and Suzan Slijpen (Slijpen Legal) for valuable cross-disciplinary comments on an earlier version of this article. Thank you Ben Rashkovich and the Yale Journal of Law & Technology for excellent suggestions and editorial support. This article benefitted from comments at the World Economic Forum Quantum Computing Ethics Workshop.

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Data delen als voorwaarde voor een succesvol AI-ecosysteem

Trainingsdatasets voor kunstmatige intelligentie: enkele juridische aspecten

Data delen (data sharing) of liever het vermogen om hoge kwaliteit trainingsdatasets te kunnen analyseren om een AI model -zoals een generative adversarial network- te trainen, is een voorwaarde voor een succesvol AI-ecosysteem in Nederland.

In ons turbulente technologische tijdperk nemen fysieke aanknopingspunten als papier of tastbare producten binnen de context van data -of informatie- in belang af. Informatie is niet langer aan een continent, staat of plaats gebonden. Informatietechnologie zoals kunstmatige intelligentie ontwikkelt zich in een dermate hoog tempo, dat de juridische problemen die daaruit voortvloeien in belangrijke mate onvoorspelbaar zijn. Hierdoor ontstaan -kort gezegd- problemen voor tech startups en scaleups.

In dit artikel een serie -mede in onderlinge samenhang te beschouwen aanbevelingen, suggesties en inventieve oplossingen om anno 2020 tot waardevolle nationale en Europese dataketens te komen.

Data donor codicil

Introductie van een Europees (of nationaal) data donor codicil waarmee een patiënt of consument vrijwillig data kan doneren aan de overheid en/of het bedrijfsleven, AVG-proof. Hier kunnen waardeketens worden gecreëerd door de sensor data van medische Internet of Things (IoT) apparaten en smart wearables van overheidswege te accumuleren. Anoniem of met biomarkers.

Data interoperabel en gestandaardiseerd

Unificatie van data uitwisselingsmodellen zodat deze interoperabel en gestandaardiseerd worden in het IoT. Een voorbeeld is een Europees EPD (Elektronisch Patiënten Dossier), i.e een Electronic Healthcare Record (EMR). AI certificering en standaardisatie (zoals ISO, ANSI, IEEE / IEC) dient bij voorkeur niet te worden uitgevoerd door private partijen met commerciële doelstellingen, maar door onafhankelijke openbare instanties (vergelijk het Amerikaanse FDA).

Machine generated (non) personal data

Een andere categorisering die we kunnen maken is enerzijds publieke (in handen van de overheid) machine generated (non) personal data, en private machine generated (non) personal data. Met machine generated data bedoelen we met name informatie en gegevens die continue door edge devices worden gegenereerd in het Internet of Things (IoT). Deze edge devices staan via edge (of fod) nodes (zenders) in verbinding met datacenters die samen met edge servers de cloud vormen. Deze architectuur noemen we ook wel edge computing.

Juridische dimensie

Data, of informatie heeft een groot aantal juridische dimensies. Aan data delen kleven potentieel intellectueel eigendomsrechtelijke (verbodsrecht en vergoedingsrecht), ethische, grondrechtelijke (privacy, vrijheid van meningsuiting), contractenrechtelijke en internationaal handelsrechtelijke aspecten. Juridisch eigendom op data bestaat anno 2020 niet omdat het -vanuit goederenrechtelijk oogpunt- niet als zaak wordt gekwalificeerd. Data heeft wel vermogensrechtelijke aspecten.

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What are the main requirements for AI systems in Healthcare?

Main barriers to adoptation of Artificial Intelligence in healthcare.

Absence of a specific AI law, or clear legal framework from the perspective of both professional users (A) and patients (B).

When constructing such a framework, it is important to make a distinction between the various sub-areas of healthcare, such as research and development, professional care providers and recipients of care. Because each sub-area has different needs.

Barriers for professional users.

It is simply unclear for companies and private and academic research institutes in the medical sector what is and is not allowed in the field of AI, blockchain, computer & machine vision and robotics. Both at European level and at national level. This knowledge is important for the commodification of their inventions/creations. Two practical examples are permission from Farmatec and obtaining a CE-marking.

Requirements for sustained use of AI in healthcare.

Since traceability and transparency are key within any healthcare (and food-feed) system, blockchain could play an important role in sustained use of AI in healthcare.

A EU AI Directive or Regulation should be able to implement and/or adhere to principles of Eudralex (The body of European Union legislation in the pharmaceutical sector), Good Manufacturing Practices (GMP) and Good Distribution Practices (GDP) in particular.

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