Artificial Intelligence (AI) is driving innovation in the financial investment sector, but it also poses significant challenges for protecting investors’ personal information. The extensive data requirements for robo-advice, coupled with technological security risks, insufficient user awareness, trust concerns, and the frequently ambiguous or non-compliant nature of privacy statements, present significant challenges to the protection of investor information. Both the European Union (EU) and China face these challenges, though in distinct ways, with their regulatory frameworks offering opportunities for mutual learning and advancement. To improve the protection of investor data in both regions, it is essential to strengthen legal regulations, increase oversight of robo-advisory platforms, implement innovative regulatory models, and enhance user awareness.

Emerging technologies, including artificial intelligence (AI), quantum computing, and biotechnology, hold immense promise to address critical global challenges such as climate change, public health crises, and resource depletion. However, their rapid development introduces pressing ethical, legal, and societal dilemmas, including data privacy concerns, algorithmic bias, intellectual property disputes, and the deepening of social inequities. This paper comprehensively explores these multifaceted challenges, underscoring the necessity of robust governance frameworks to mitigate associated risks. It advocates for adopting Responsible Research and Innovation (RRI) principles to ensure technological progress aligns with societal values, ethical standards, and sustainability objectives. Through actionable policy recommendations and a comprehensive governance model, the paper emphasizes the importance of international collaboration and inclusive stakeholder engagement in shaping the responsible trajectory of technological innovation.

This article considers possible misunderstandings of cryptoasset investments by consumers in Turkey and possible legal responses to them. Building upon interviews with Turkish professionals and investors in a study in the empirical legal tradition it considers the potential for three misunderstandings, framed as expectation gaps. First, it considers that many consumers can be led into unwise investments through expectation gaps based on suppositions that the safeguards, such as deposit protection, that apply to other investment opportunities will be present. Second, it considers that others will have expectation gaps based on stories of success for others bringing survivorship bias combined with a fear of missing out. Third, it finds that, although stablecoins are often regarded as a safe investment, there is another expectation gap, as they can lack the protections that might be expected. In discussing the expectation gaps we draw upon an analysis of the terms of service of the 10 leading Turkish crypto exchanges. The article also considers how cryptoassets are being used in Turkey and notes that many Turkish investors find cryptoassets to offer significant positives. Nonetheless, it finds that in some cases significant assets can be put at risk due to the expectation gaps and other misunderstandings, potentially impacting on families and livelihoods. It examines the Turkish Capital Markets Law, which was amended in 2024, after the empirical studies were carried out. It considers how its approach offers improved protection, although it is found to be much less detailed than the EU’s Markets in Crypto Assets Regulation. It highlights one area in which the Turkish law might have a chilling effect on crypto firms, which can potentially damage the development of this sector in Turkey. It then sets out a preferred pluralistic and decentred regulatory approach based on improvement of consumer understanding of cryptoassets.

Chinese regulators have intensified their supervision over personal information collection and utilization, following the promulgation of the Personal Information Protection Law (PIPL) and other data protection regulations in November 2021. Whilst regulators primarily rely on data flows to identify suspicious activities in data collection and transfer during and after the use of apps, there is still a lack of protection measures to prevent privacy breaches. Privacy policies are important for enhancing the prevention and protection of the privacy rights and interests of app users, as well as for fostering self-regulation among operators. However, privacy policies are often lengthy and replete with vague expressions, making it difficult for users to read and thus inadequate for safeguarding users' information rights. It is crucial to address the power imbalance between operators and users and to assess the legality of app privacy policies formulated by operators. This paper introduces a methodology for evaluating the legality of privacy policies based on legal knowledge. First, we collected policy texts and constructed the Children's Privacy Policy Corpus (CCPP-181) that covers a variety of privacy policies for children's apps. Then, we proposed a legality evaluation method grounded in regulatory standards, and applied it to annotate CCPP-181 corpus annotation. After three rounds of annotation, 20.2% of the 1160 sentences in the corpus were identified to have legality problems. Based on the legal text analysis method, this paper analyzes the legality issues in app privacy policies, in order to eliminate the inequality of app privacy policies and protect user data security.

This article reports on a study of the adaptability of European Union (EU) roadside enforcement powers to automated vehicles (AVs). It identifies technological obsolescence within EU laws where there are powers to stop vehicles being directed to the ‘driver’, ‘road users’ or ‘traffic participant’ all of which are assumed to be a ‘human’ controlling a vehicle. This is problematic in an automated transport future where automated driving systems (ADS) will increasingly be in control of the dynamic driving tasks. This article concludes that instead of ‘human-centric’ roadside enforcement powers, lawmakers should move to a ‘vehicle-centric’ focus, where the vehicle (irrespective of who, or what, is driving) should be the addressee of the legal power and provides examples of reform directions.

The pervasive risk of bias in generative artificial intelligence (AI) systems necessitates robust measures to protect public rights and enhance regulatory effectiveness. Addressing bias across the lifecycle of AI products—from data collection and training to modeling and application—requires legal and technical strategies tailored to each layer of potential bias. Current regulatory frameworks, such as China's “Interim Measures for the Administration of Generative AI Service,” lack specific guidelines to mitigate bias in AI decision-making. Global regulatory frameworks are still developing, underscoring the need for a comprehensive governance structure that defines the scope of regulation, implements layered measures to address bias, and allocates liability among platform developers.