EU Artificial Intelligence Act: The European Approach to AI

Stanford - Vienna Transatlantic Technology Law Forum, Transatlantic Antitrust and IPR Developments, Stanford University, Issue No. 2/2021

New Stanford tech policy research: “EU Artificial Intelligence Act: The European Approach to AI”.

Download the article here: Kop_EU AI Act: The European Approach to AI

EU regulatory framework for AI

On 21 April 2021, the European Commission presented the Artificial Intelligence Act. This Stanford Law School contribution lists the main points of the proposed regulatory framework for AI.

The Act seeks to codify the high standards of the EU trustworthy AI paradigm, which requires AI to be legally, ethically and technically robust, while respecting democratic values, human rights and the rule of law. The draft regulation sets out core horizontal rules for the development, commodification and use of AI-driven products, services and systems within the territory of the EU, that apply to all industries.

Legal sandboxes fostering innovation

The EC aims to prevent the rules from stifling innovation and hindering the creation of a flourishing AI ecosystem in Europe. This is ensured by introducing various flexibilities, including the application of legal sandboxes that afford breathing room to AI developers.

Sophisticated ‘product safety regime’

The EU AI Act introduces a sophisticated ‘product safety framework’ constructed around a set of 4 risk categories. It imposes requirements for market entrance and certification of High-Risk AI Systems through a mandatory CE-marking procedure. To ensure equitable outcomes, this pre-market conformity regime also applies to machine learning training, testing and validation datasets.

Pyramid of criticality

The AI Act draft combines a risk-based approach based on the pyramid of criticality, with a modern, layered enforcement mechanism. This means, among other things, that a lighter legal regime applies to AI applications with a negligible risk, and that applications with an unacceptable risk are banned. Stricter regulations apply as risk increases.

Enforcement at both Union and Member State level

The draft regulation provides for the installation of a new enforcement body at Union level: the European Artificial Intelligence Board (EAIB). At Member State level, the EAIB will be flanked by national supervisors, similar to the GDPR’s oversight mechanism. Fines for violation of the rules can be up to 6% of global turnover, or 30 million euros for private entities.

CE-marking for High-Risk AI Systems

In line with my recommendations, Article 49 of the Act requires high-risk AI and data-driven systems, products and services to comply with EU benchmarks, including safety and compliance assessments. This is crucial because it requires AI infused products and services to meet the high technical, legal and ethical standards that reflect the core values of trustworthy AI. Only then will they receive a CE marking that allows them to enter the European markets. This pre-market conformity mechanism works in the same manner as the existing CE marking: as safety certification for products traded in the European Economic Area (EEA).

Trustworthy AI by Design: ex ante and life-cycle auditing

Responsible, trustworthy AI by design requires awareness from all parties involved, from the first line of code. Indispensable tools to facilitate this awareness process are AI impact and conformity assessments, best practices, technology roadmaps and codes of conduct. These tools are executed by inclusive, multidisciplinary teams, that use them to monitor, validate and benchmark AI systems. It will all come down to ex ante and life-cycle auditing.

The new European rules will forever change the way AI is formed. Pursuing trustworthy AI by design seems like a sensible strategy, wherever you are in the world.

Meer lezen

Artificial Intelligence, Artificiële Intelligentie, Certification, European Law, Europees recht, Kunstmatige Intelligentie, Machine Learning, Stanford, WetgevingMauritz Kop25 september 2021Stanford Law SchoolEU Artificial Intelligence Act, regulatory framework, Pyramid of criticality, pre-market conformity, CE-marking, Certification, Risk-based approach, High-Risk AI Systems, Impact Assessment, Trustworthy AI by Design, life-cycle auditing, Ethics and Responsible AI, Worldwide standards, Extraterritorial effect, Fourth Industrial Revolution, Data Act, GDPR, FFD, MDR, Awareness, Stanford - Vienna Transatlantic Technology Law Forum, Stanford University, European Commission, Product safety regime, Machine learning trainingdatasets, Democratic values, human rights, rule of law, legal sandboxes, innovation, flourishing AI-ecosystem, Legal Compliance

Quantum Computing and Intellectual Property Law

Berkeley Technology Law Journal, Vol. 35, No. 3, 2021

New Stanford University Beyond IP Innovation Law research article: “Quantum Computing and Intellectual Property Law”.

By Mauritz Kop

Citation: Kop, Mauritz, Quantum Computing and Intellectual Property Law (April 8, 2021). Berkeley Technology Law Journal 2021, Vol. 35, No. 3, pp 101-115, February 8, 2022, https://btlj.org/2022/02/quantum-computing-and-intellectual-property-law/

Download the article here: Kop_QC and IP Law BTLJ

Please find a short abstract below:

Intellectual property (IP) rights & the Quantum Computer

What types of intellectual property (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? The article explores possible answers to these tantalizing questions.

IP overprotection leads to exclusive exploitation rights for first movers

The article demonstrates that strategically using a mixture of IP rights to maximize the value of the IP portfolio of the quantum computer’s owner, potentially leads to IP protection in perpetuity. Overlapping IP protection regimes can result in unlimited duration of global exclusive exploitation rights for first movers, being a handful of universities and large corporations. The ensuing IP overprotection in the field of quantum computing leads to an unwanted concentration of market power. Overprotection of information causes market barriers and hinders both healthy competition and industry-specific innovation. In this particular case it slows down progress in an important application area of quantum technology, namely quantum computing.

Fair competition and antitrust laws for quantum technology

In general, our current IP framework is not written with quantum technology in mind. IP should be an exception -limited in time and scope- to the rule that information goods can be used for the common good without restraint. IP law cannot incentivize creation, prevent market failure, fix winner-takes-all effects, eliminate free riding and prohibit predatory market behavior at the same time. To encourage fair competition and correct market skewness, antitrust law is the instrument of choice.

Towards an innovation architecture that mixes freedom and control

The article proposes a solution tailored to the exponential pace of innovation in The Quantum Age, by introducing shorter IP protection durations of 3 to 10 years for Quantum and AI infused creations and inventions. These shorter terms could be made applicable to both the software and the hardware side of things. Clarity about the recommended limited durations of exclusive rights -in combination with compulsory licenses or fixed prized statutory licenses- encourages legal certainty, knowledge dissemination and follow on innovation within the quantum domain. In this light, policy makers should build an innovation architecture that mixes freedom (e.g. access, public domain) and control (e.g. incentive & reward mechanisms).

Creating a thriving global quantum ecosystem

The article concludes that anticipating spectacular advancements in quantum technology, the time is now ripe for governments, research institutions and the markets to prepare regulatory and IP strategies that strike the right balance between safeguarding our fundamental rights & freedoms, our democratic norms & standards, and pursued policy goals that include rapid technology transfer, the free flow of information and the creation of a thriving global quantum ecosystem, whilst encouraging healthy competition and incentivizing sustainable innovation.

Meer lezen

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.

Meer lezen

Shaping the Law of AI: Transatlantic Perspectives

Stanford-Vienna Transatlantic Technology Law Forum, TTLF Working Papers No. 65, Stanford University (2020).

New Stanford innovation policy research: “Shaping the Law of AI: Transatlantic Perspectives”.

Download the article here: Kop_Shaping the Law of AI-Stanford Law

The race for AI dominance

The race for AI dominance is a competition in values, as much as a competition in technology. In light of global power shifts and altering geopolitical relations, it is indispensable for the EU and the U.S to build a transatlantic sustainable innovation ecosystem together, based on both strategic autonomy, mutual economic interests and shared democratic & constitutional values. Discussing available informed policy variations to achieve this ecosystem, will contribute to the establishment of an underlying unified innovation friendly regulatory framework for AI & data. In such a unified framework, the rights and freedoms we cherish, play a central role. Designing joint, flexible governance solutions that can deal with rapidly changing exponential innovation challenges, can assist in bringing back harmony, confidence, competitiveness and resilience to the various areas of the transatlantic markets.

25 AI & data regulatory recommendations

Currently, the European Commission (EC) is drafting its Law of AI. This article gives 25 AI & data regulatory recommendations to the EC, in response to its Inception Impact Assessment on the “Artificial intelligence – ethical and legal requirements” legislative proposal. In addition to a set of fundamental, overarching core AI rules, the article suggests a differentiated industry-specific approach regarding incentives and risks.

European AI legal-ethical framework

Lastly, the article explores how the upcoming European AI legal-ethical framework’s norms, standards, principles and values can be connected to the United States, from a transatlantic, comparative law perspective. When shaping the Law of AI, we should have a clear vision in our minds of the type of society we want, and the things we care so deeply about in the Information Age, at both sides of the Ocean.

Meer lezen

We hebben dringend een recht op dataprocessing nodig

Deze column 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-dringend-recht-dataprocessing-nodig/

5 juridische obstakels voor een succesvol AI-ecosysteem

Eerder schreef ik dat vraagstukken over het (intellectueel) eigendom van data, databescherming en privacy een belemmering vormen voor het (her)gebruiken en delen van hoge kwaliteit data tussen burgers, bedrijven, onderzoeksinstellingen en de overheid. Er bestaat in Europa nog geen goed functionerend juridisch-technisch systeem dat rechtszekerheid en een gunstig investeringsklimaat biedt en bovenal is gemaakt met de datagedreven economie in het achterhoofd. We hebben hier te maken met een complex probleem dat in de weg staat aan exponentiële innovatie.

Auteursrechten, Privacy en Rechtsonzekerheid over eigendom van data

De eerste juridische horde bij datadelen is auteursrechtelijk van aard. Ten tweede kunnen er (sui generis) databankenrechten van derden rusten op (delen van) de training-, testing- of validatiedataset. Ten derde zullen bedrijven na een strategische afweging kiezen voor geheimhouding, en niet voor het patenteren van hun technische vondst. Het vierde probleempunt is rechtsonzekerheid over juridisch eigendom van data. Een vijfde belemmering is de vrees voor de Algemene verordening gegevensbescherming (AVG). Onwetendheid en rechtsonzekerheid resulteert hier in risicomijdend gedrag. Het leidt niet tot spectaculaire Europese unicorns die de concurrentie aankunnen met Amerika en China.

Wat is machine learning eigenlijk?

Vertrouwdheid met technische aspecten van data in machine learning geeft juristen, datawetenschappers en beleidsmakers de mogelijkheid om effectiever te communiceren over toekomstige regelgeving voor AI en het delen van data.

Machine learning en datadelen zijn van elementair belang voor de geboorte en de evolutie van AI. En daarmee voor het behoud van onze democratische waarden, welvaart en welzijn. Een machine learning-systeem wordt niet geprogrammeerd, maar getraind. Tijdens het leerproces ontvangt een computer uitgerust met kustmatige intelligentie zowel invoergegevens (trainingdata), als de verwachte, bij deze inputdata behorende antwoorden. Het AI-systeem moet zelf de bijpassende regels en wetmatigheden formuleren met een kunstmatig brein. Algoritmische, voorspellende modellen kunnen vervolgens worden toegepast op nieuwe datasets om nieuwe, correcte antwoorden te produceren.

Dringend nodig: het recht op dataprocessing

De Europese Commissie heeft de ambitie om datasoevereiniteit terug te winnen. Europa moet een internationale datahub worden. Dit vereist een modern juridisch raamwerk in de vorm van de Europese Data Act, die in de loop van 2021 wordt verwacht. Het is naar mijn idee cruciaal dat de Data Act een expliciet recht op dataprocessing bevat.

Technologie is niet neutraal

Tegelijkertijd kan de architectuur van digitale systemen de sociaal-maatschappelijke impact van digitale transformatie reguleren. Een digitaal inclusieve samenleving moet technologie actief vormgeven. Technologie an sich is namelijk nooit neutraal. Maatschappelijke waarden zoals transparantie, vertrouwen, rechtvaardigheid, controle en cybersecurity moeten worden ingebouwd in het design van AI-systemen en de benodigde trainingdatasets, vanaf de eerste regel code.

Meer lezen

The Right to Process Data for Machine Learning Purposes in the EU

Harvard Law School, Harvard Journal of Law & Technology (JOLT) Volume 34, Digest Spring 2021

New interdisciplinary Stanford University AI & Law research article: “The Right to Process Data for Machine Learning Purposes in the EU”.

Download the article here: Kop_The Right to Process Data-Harvard

Data Act & European data-driven economy

Europe is now at a crucial juncture in deciding how to deploy data driven technologies in ways that encourage democracy, prosperity and the well-being of European citizens. The upcoming European Data Act provides a major window of opportunity to change the story. In this respect, it is key that the European Commission takes firm action, removes overbearing policy and regulatory obstacles, strenuously harmonizes relevant legislation and provides concrete incentives and mechanisms for access, sharing and re-use of data. The article argues that to ensure an efficiently functioning European data-driven economy, a new and as yet unused term must be introduced to the field of AI & law: the right to process data for machine learning purposes.

The state can implement new modalities of property

Data has become a primary resource that should not be enclosed or commodified per se, but used for the common good. Commons based production and data for social good initiatives should be stimulated by the state. We need not to think in terms of exclusive, private property on data, but in terms of rights and freedoms to use, (modalities of) access, process and share data. If necessary and desirable for the progress of society, the state can implement new forms of property. Against this background the article explores normative justifications for open innovation and shifts in the (intellectual) property paradigm, drawing inspiration from the works of canonical thinkers such as Locke, Marx, Kant and Hegel.

Ius utendi et fruendi for primary resource data

The article maintains that there should be exceptions to (de facto, economic or legal) ownership claims on data that provide user rights and freedom to operate in the setting of AI model training. It concludes that this exception is conceivable as a legal concept analogous to a quasi, imperfect usufruct in the form of a right to process data for machine learning purposes. A combination of usus and fructus (ius utendi et fruendi), not for land but for primary resource data. A right to process data that works within the context of AI and the Internet of Things (IoT), and that fits in the EU acquis communautaire. Such a right makes access, sharing and re-use of data possible, and helps to fulfil the European Strategy for Data’s desiderata.

Meer lezen

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’.

Download the article here: Kop_Machine Learning and EU Data Sharing Practices-Stanford University

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.

Meer lezen

Mauritz Kop becomes TTLF Fellow at Stanford University

AIRecht Partner joins Stanford Law School’s Transatlantic Thinktank

Honoured and thrilled to join Stanford Law School’s Transatlantic Thinktank and become TTLF Fellow at Stanford University. It is the Silicon Valley, California based Transatlantic Technology Law Forum’s objective to raise professional understanding and public awareness of transatlantic challenges in the field of law, science and technology, as well as to support policy-oriented research on transatlantic issues in the field.

Human Centred AI & IPR policy

My comparative, interdisciplinary research project focuses on Human Centred AI & IPR policy. How to realize an impactful transformative tech related IP (intellectual property) policy that facilitates an innovation optimum and protects our common Humanist moral values at the same time?

Focus beyond Intellectual Property Law

With an additional focus beyond IP, the research shall present ideas on how Europe and The United States could apply sustainable disruptive innovation policy pluralism (i.e. mix, match and layer IP alternatives such as competition law and government-market hybrids) to enable fair-trading conditions and balance the effects of exponential innovation within the Transatlantic markets. The research envisages that the presented ideas and viewpoints will be refined towards more actual policies in Brussels and Washington.

Meer lezen

Intellectual Property at Stanford Law School

USA IP Law at Stanford University

Stanford Law School has a long-standing tradition of sharing its expertise in Intellectual Property, Science and Technology law with legal professionals from around the world. In August 2019, AIRecht managing partner and strategic IP specialist Mauritz Kop had the pleasure to be part of a pre-selected international group of highly talented IP lawyers, counsels and scholars who had the opportunity to bring their professional skills to the next level and study complex IP issues related to Silicon Valley’s hi-tech industry, during an intensive international certificate summer program on U.S. IP law. The international professional American Intellectual Property Law Program at Stanford University is co-directed by Prof. Siegfried Fina, Prof. Mark Lemley and Dr. Roland Vogl.

SLS: A World’s Leading Law School at an Ivy Plus League University

Stanford University is an Ivy Plus League university. Ivy League schools such as Harvard, Yale, Princeton, MIT and Columbia University are viewed as the most prestigious, ranked among the best universities worldwide and have connotations of academic excellence. SLS is one of the world’s leading law schools. The Faculty draws international top talent to its magnificent campus. Stanford Law School’s Program in Law, Science & Technology (LST) has been ranked regularly among the top three intellectual property law programs in the United States, together with the IP Programs (LL.M. and J.D.) of the University of California-Berkeley and the University of New York.

Meer lezen

Silicon Valley: AI Impact Assessment presented at Apple, Facebook and Stanford University

AIRecht presents ECP AIIA in Silicon Valley

On 23 August 2019, Mauritz Kop LL.M. had the honour to present the ECP AI Impact Assessment to front-running companies in Silicon Valley, in the amazing San Francisco Bay Area. AI should be a force for good and our Dutch risk-management tool can help with that. The AIIA is a first-of-its-kind guide for the development and implementation of artificial intelligence and includes 2 things: a practical Checklist from a legal, technical and ethical point of view (in line with the EU Trustworthy AI paradigm) and a concrete Code of Conduct for data scientists. On top of that, our AIRecht managing partner introduced the AIIA at Stanford University, in beautiful Palo Alto.

Stanford University Campus

Stanford University has a stunning campus. It offers exuberant nature, nice temperature and magnificent architecture. Innovation is in the air. During the graduation ceremony of a post-doctoral intellectual property course at Stanford Law School, Mauritz officially handed over an English hardcopy of the ECP AI Impact Assessment to Professor Siegfried Fina and Professor Roland Vogl, Program Directors at SLS. The Program focusses on ‘'Overview on U.S. IP Law’ with specific attention to high-tech IP issues, such as copyrights, trade secrets, patents, trademarks, licensing and venture capital. A wonderful place for learning, discovery, innovation, expression and discourse, at the highest academic level imaginable.

Transatlantic bridges

It was an incredibly inspiring visit to Silicon Valley. We have seen it with our own eyes now: the Bay Area truly is the innovation hub of the world, together with Massachusetts (Boston, Harvard, MIT). It offers excellent opportunities for tech start-ups to work together and brainstorm with the best qualified experts, and create partnerships with professionals in myriad industrial sectors and disciplines. We hope to be back soon to further strengthen EU-USA relationships, construct new partnerships, exchange talent and remove barriers to trade and collaboration across the Atlantic.

Meer lezen

Amerikaans recht, Artificial Intelligence, Auteursrecht, Fundamental Rights, Healthcare, Intellectueel Eigendom, University, Tech StartupsMauritz Kop12 november 2019AIRechtartificial intelligence, AI Impact Assessment, Apple, Facebook, Innovation Optimum, intellectual property, Stanford University

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

EU regulatory framework for AI

Legal sandboxes fostering innovation

Sophisticated ‘product safety regime’

Pyramid of criticality

Enforcement at both Union and Member State level

CE-marking for High-Risk AI Systems

Trustworthy AI by Design: ex ante and life-cycle auditing

Intellectual property (IP) rights & the Quantum Computer

IP overprotection leads to exclusive exploitation rights for first movers

Fair competition and antitrust laws for quantum technology

Towards an innovation architecture that mixes freedom and control

Creating a thriving global quantum ecosystem

What is quantum technology?

Raising Quantum Awareness

Connecting AI and Nanotechnology to Quantum

Risk-based Quantum Technology Impact Assessment Tools

The race for AI dominance

25 AI & data regulatory recommendations

European AI legal-ethical framework

5 juridische obstakels voor een succesvol AI-ecosysteem

Auteursrechten, Privacy en Rechtsonzekerheid over eigendom van data

Wat is machine learning eigenlijk?

Dringend nodig: het recht op dataprocessing

Technologie is niet neutraal

Data Act & European data-driven economy

The state can implement new modalities of property

Ius utendi et fruendi for primary resource data

Supervised machine learning needs annotated training datasets

Legal reform and data-driven economy

Freedom of expression and information, public domain, competition law

Data protection and privacy

Modalities of future AI-regulation

AIRecht Partner joins Stanford Law School’s Transatlantic Thinktank

Human Centred AI & IPR policy

Focus beyond Intellectual Property Law

USA IP Law at Stanford University

SLS: A World’s Leading Law School at an Ivy Plus League University

AIRecht presents ECP AIIA in Silicon Valley

Stanford University Campus

Transatlantic bridges

Juridische diensten en projecten in Nederland en daarbuiten