# Data driven regulation `kaal:entity:data-driven-regulation` **Status.** derived This node is assembled mechanically from the 8 claims that carry the concept tag `data-driven-regulation`. It is a roster of what the corpus says under this term. It is **not** an adjudicated definition: no single statement here has been ruled canonical, and no first-appearance call has been made. Read the claims and judge for yourself. ## Every claim under this term 8 claims across 2 works, 2016 to 2017. **2016** - [2808132-048](https://wulfkaal.github.io/claims/2808132-048) [design/argued] -- Regulators should take anticipatory measures only after cross-validation and triangulation, that is, when multiple independent data analyses point unanimously toward a specific demand for regulatory action. > high-quality, decentralized, and real-time information for rulemaking. If and when multiple data analyses together point unanimously in the direction of a certain demand for regulatory action, regulators should take anticipatory measures after cross-validation Wulf A. Kaal, Erik P.M. Vermeulen, How to Regulate Disruptive Innovation - From Facts to Data (2016). SSRN: https://ssrn.com/abstract=2808132 - [2808132-049](https://wulfkaal.github.io/claims/2808132-049) [failure/asserted] *(failure mode)* -- No regulatory processes or data evaluation capabilities currently exist that could carry out the cross-validated analyses and support the anticipatory regulatory action the authors propose. > and triangulation. Currently no regulatory processes and data evaluation exist that could facilitate such analyses and anticipatory regulatory action. Wulf A. Kaal, Erik P.M. Vermeulen, How to Regulate Disruptive Innovation - From Facts to Data (2016). SSRN: https://ssrn.com/abstract=2808132 - [2808132-052](https://wulfkaal.github.io/claims/2808132-052) [design/argued] -- Venture capital investment allocation data can help facilitate anticipatory regulation of disruptive innovation, but it is only one of several emerging data sources usable for signaling in regulatory process optimization. > facilitate anticipatory regulation associated with disruptive innovation, but it emphasizes that VC investment allocation data is only one form of the emerging data sources that can be used as signaling for regulatory process optimization. Other data sources are and may Wulf A. Kaal, Erik P.M. Vermeulen, How to Regulate Disruptive Innovation - From Facts to Data (2016). SSRN: https://ssrn.com/abstract=2808132 **2017** - [2834531-029](https://wulfkaal.github.io/claims/2834531-029) [normative/argued] -- The response to contested facts should not be to abandon facts, but to identify alternative grounds for regulation that would make the regulation of innovative products and services more effective and more legitimate. > And yet, rather than abandoning facts, we should be thinking about some alternative grounds for regulation that would allow the regulation of innovative products and services to be more effective and legitimate. Mark Fenwick, Wulf A. Kaal, Erik P. M. Vermeulen, Regulation Tomorrow What Happens When Technology Is Faster Than the Law (2017). SSRN: https://ssrn.com/abstract=2834531 - [2834531-032](https://wulfkaal.github.io/claims/2834531-032) [design/argued] -- Data on investment in new technology can be used as an index or proxy for the necessity of regulation, supplying the signal that fact based regulation cannot generate in time. > Of particular importance in this context, is data relating to investment in new technology and innovation.90 Such data can be used as an index or proxy of the necessity of regulation. Mark Fenwick, Wulf A. Kaal, Erik P. M. Vermeulen, Regulation Tomorrow What Happens When Technology Is Faster Than the Law (2017). SSRN: https://ssrn.com/abstract=2834531 - [2834531-033](https://wulfkaal.github.io/claims/2834531-033) [design/argued] -- Using investment data would let regulators act proactively, avoid wasting resources on technologies unlikely to reach the market, and define the scope of a technology more accurately by focusing on the type of firm attracting investor attention. > This might then allow regulators to be more pro–active and avoid wasting resources on technologies that are unlikely to make it to market. It would also allow regulators to more accurately define the scope of a technology by focusing on the type of firm that is attracting attention. Mark Fenwick, Wulf A. Kaal, Erik P. M. Vermeulen, Regulation Tomorrow What Happens When Technology Is Faster Than the Law (2017). SSRN: https://ssrn.com/abstract=2834531 - [2834531-034](https://wulfkaal.github.io/claims/2834531-034) [empirical/argued] -- Data on the timing of investment is a reliable indicator of a technology's commercial maturity, because high levels of investor activity signal that the technology is about to be ready for commercial exploitation, which tells regulators when to intervene. > Data on the timing of investment appears to provide a reliable indicator of the commercial maturity of a technology, in the sense that high levels of investor activity indicate that a particular technology is about to be ready for commercial exploitation. Mark Fenwick, Wulf A. Kaal, Erik P. M. Vermeulen, Regulation Tomorrow What Happens When Technology Is Faster Than the Law (2017). SSRN: https://ssrn.com/abstract=2834531 - [2834531-044](https://wulfkaal.github.io/claims/2834531-044) [condition/argued] -- A data based regulatory environment requires measures built on flexible and inclusive processes that involve startups and established companies, regulators, experts, and the public. > In a data–based regulatory environment there is a clear need for measures that are built on flexible and inclusive processes that involve startups and established companies, regulators, experts and the public. Mark Fenwick, Wulf A. Kaal, Erik P. M. Vermeulen, Regulation Tomorrow What Happens When Technology Is Faster Than the Law (2017). SSRN: https://ssrn.com/abstract=2834531 ## Verify Every claim above resolves to a record carrying a verbatim source quote, the sha256 of the source PDF, and a preformatted citation. Nothing here asks to be taken on trust. curl -s https://wulfkaal.github.io/entities/data-driven-regulation.md | sha256sum **Canonical form.** This markdown file is the canonical hashed representation of this entity node. Its sha256 is the content hash.