# Trial and error `kaal:entity:trial-and-error` **Status.** derived This node is assembled mechanically from the 10 claims that carry the concept tag `trial-and-error`. 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 10 claims across 3 works, 2013 to 2016. **2013** - [2267560-006](https://wulfkaal.github.io/claims/2267560-006) [failure/argued] *(failure mode)* -- Trial-and-error rulemaking is suboptimal because participating actors acquire the necessary information ex-post, only after rules have turned out to be suboptimal, rather than increasing the availability of relevant information ex-ante. > is suboptimal for rulemaking because, rather than increasing the availability of relevant information ex-ante (through a dynamic process as proposed in this paper), participating actors acquire the necessary information ex-post after rules turn out to be suboptimal. Wulf A. Kaal, Evolution of Law Dynamic Regulation in a New Institutional Economics Framework (2013). SSRN: https://ssrn.com/abstract=2267560 - [2267560-008](https://wulfkaal.github.io/claims/2267560-008) [mechanism/argued] -- Supplementing the rulemaking process with dynamic elements increases the public rulemaker's ability to adapt public rules to unknown future states, and thereby curtails public trial-and-error rulemaking. > Supplementing the rulemaking process with dynamic elements expands the availability of relevant information and increases the public rulemaker's ability to adapt public rules to unknown future states. Wulf A. Kaal, Evolution of Law Dynamic Regulation in a New Institutional Economics Framework (2013). SSRN: https://ssrn.com/abstract=2267560 - [2267560-020](https://wulfkaal.github.io/claims/2267560-020) [failure/argued] *(failure mode)* -- In the conventional NIE learning process, the requirements for rules and their adaptability to future states become clear only after stable and presumptively optimal rules have already emerged as suboptimal, so anticipation of future developments plays no role and learning is confined to learning from mistakes. > Anticipation of future developments does not play a role in this learning process. Wulf A. Kaal, Evolution of Law Dynamic Regulation in a New Institutional Economics Framework (2013). SSRN: https://ssrn.com/abstract=2267560 - [2267560-051](https://wulfkaal.github.io/claims/2267560-051) [mechanism/argued] -- The combination of multiple feedback processes results in a sequence of mutually-reinforcing, information-enhancing events that minimizes ex-post trial-and-error experimentation with stable rules after those rules have already emerged as failures. > The combination of these feedback processes can result in a sequence of mutually-reinforcing, information- enhancing events. This process can help minimize ex-post trial-and-error experimentation with stable and presumptively optimal rules after previous stable rules have emerged as failures. Wulf A. Kaal, Evolution of Law Dynamic Regulation in a New Institutional Economics Framework (2013). SSRN: https://ssrn.com/abstract=2267560 **2014** - [kaal-2014-dynamicregulationviagove-002](https://wulfkaal.github.io/claims/kaal-2014-dynamicregulationviagove-002) [mechanism/argued] -- Anticipatory dynamic elements in regulation reduce the need for costly and suboptimal ex post trial and error experimentation with stable and presumptively optimal rules. > Anticipatory dynamic elements in regulation can help minimize costly and suboptimal ex-post trial-and-error experimentation with stable and presump- tively optimal rules. Kaal, Dynamic Regulation via Governmental Contracts (2014) - [kaal-2014-dynamicregulationviagove-015](https://wulfkaal.github.io/claims/kaal-2014-dynamicregulationviagove-015) [failure/argued] *(failure mode)* -- The trial and error approach to rulemaking structurally prevents rulemakers from obtaining relevant information ex ante, before rules are enacted. > The trial-and-error approach53 to rulemaking does not allow rulemakers to attain relevant information for rule- making ex-ante, before rules are enacted. Kaal, Dynamic Regulation via Governmental Contracts (2014) - [kaal-2014-dynamicregulationviagove-019](https://wulfkaal.github.io/claims/kaal-2014-dynamicregulationviagove-019) [predictive/argued] -- Trial and error rulemaking could become obsolete if dynamic elements in rulemaking processes systematically anticipated future contingencies and the corresponding regulatory needs. > Trial-and-error-rulemaking could become obsolete if dynamic ele- ments in rulemaking processes systematically anticipated future contingencies and corresponding regulatory needs. Kaal, Dynamic Regulation via Governmental Contracts (2014) **2016** - [2808132-002](https://wulfkaal.github.io/claims/2808132-002) [failure/argued] *(failure mode)* -- Ex post facts-based, trial-and-error rulemaking combined with stable and presumptively optimal rules often produces suboptimal regulatory outcomes, and those outcomes are no longer sustainable in an environment of exponential disruptive innovation. > of these. The ex-post facts-based and trial-and-error-rulemaking with stable and presumptively optimal rules7 in the existing regulatory framework8 often produces suboptimal regulatory outcomes that are no longer sustainable in an environment of Wulf A. Kaal, Erik P.M. Vermeulen, How to Regulate Disruptive Innovation - From Facts to Data (2016). SSRN: https://ssrn.com/abstract=2808132 - [2808132-028](https://wulfkaal.github.io/claims/2808132-028) [mechanism/argued] *(failure mode)* -- The collective action problem of rulemaking, the problems of trial-and-error rulemaking, and the problems of regulatory cycles derive largely from the nature of stable and presumptively optimal rules themselves, not from unrelated institutional defects. > problems associated with trial-and-error rulemaking, and problems associated with regulatory cycles derive largely from the nature of stable and presumptively optimal rules.108 Rulemaking with dynamic elements increases the use of institution-specific, Wulf A. Kaal, Erik P.M. Vermeulen, How to Regulate Disruptive Innovation - From Facts to Data (2016). SSRN: https://ssrn.com/abstract=2808132 - [2808132-030](https://wulfkaal.github.io/claims/2808132-030) [mechanism/argued] -- Regulatory cycles and trial-and-error rulemaking become less prevalent under adaptive rulemaking because adaptive capabilities supplement stable rules, making rule revisions less frequent. > Similarly, regulatory cycles and trial-and-error rulemaking become less prevalent because adaptive rulemaking processes supplement stable rules with adaptive capabilities that make rule revisions less prevalent and minimize trial-and error rulemaking. Wulf A. Kaal, Erik P.M. Vermeulen, How to Regulate Disruptive Innovation - From Facts to Data (2016). SSRN: https://ssrn.com/abstract=2808132 ## 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/trial-and-error.md | sha256sum **Canonical form.** This markdown file is the canonical hashed representation of this entity node. Its sha256 is the content hash.