- From: Paola Di Maio <paoladimaio10@gmail.com>
- Date: Thu, 29 Oct 2020 21:03:23 +0800
- To: carl mattocks <carlmattocks@gmail.com>
- Cc: W3C AIKR CG <public-aikr@w3.org>
- Message-ID: <CAMXe=SqB5tPZu+qcEqMZUyvhqYrVMcFaQVQL9kOuAicHrwbk5A@mail.gmail.com>
I dont see a problem with that, if that is enough to serve the purpose but unless you or Owen are going to JAND curate and maintain the register (Which would be difficult because you may not know of all the systems in use) you have to sell the idea to the ine stakeholders unless the register is mandatory by law across all possible jurisdictions which I dont expect to happen But let us know how you want to shape this vision further I still have not figured a way, will share when I do P On Thu, Oct 29, 2020 at 8:48 PM carl mattocks <carlmattocks@gmail.com> wrote: > The core of our proposal for the Register of AI Systems (RAIS) would > leverage the insights gained using StratML for AI KR. > > Simply put, core elements of RAIS include those used to explain Strategy, > value chain, objectives, goals, KR utilization and KPIs that measure > output / outcome. > > cheers > Carl > > It was a pleasure to clarify > > > On Wed, Oct 28, 2020 at 9:04 PM Paola Di Maio <paola.dimaio@gmail.com> > wrote: > >> Thank you Carl >> Yesterday a report was published on this theme >> https://automatingsociety.algorithmwatch.org/ >> >> Both Governance and explainability are open issues >> If you couLD put together a concrete proposal, we can send it out as a WG >> >> But we need to discuss it, I am not sure a registry would cover all the >> instances >> and it would be an administrative overhead. >> >> Shall we open a draft and discuss some possibilities? >> PDM >> >> >> >> >> On Thu, Oct 29, 2020 at 1:38 AM carl mattocks <carlmattocks@gmail.com> >> wrote: >> >>> Executive summary Mind the gap: How to fill the equality and AI >>> accountability gap in an automated world Institute for the Future of Work >>> Governance and regulation We need a new approach to governance and >>> regulation of data-driven, machine-based decision making. This approach >>> must be principle-driven and human-centred, work across the entire >>> innovation cycle, shift our emphasis to preventative action, and align our >>> legal regimes and regulators. ... >>> >>> https://uploads-ssl.webflow.com/5f57d40eb1c2ef22d8a8ca7e/5f9850d5410374c05fdc9a84_IFOW-ETF-Report-(v7-27.10.20).pdf >>> >>> .. the Institute for the Future of Work established a >>> cross-disciplinary Equality Task Force (ETF) to examine how algorithms and >>> artificial intelligence impact equality and fairness at work >>> >>> .. encourage systematic mapping of deployment and register of systems >>> involving some uses of algorithmic AI and ML systems to inform the public >>> and policy-making debates, ... >>> >>> enjoy >>> >>> Carl Mattocks >>> co-chair AIKRCG >>> >>> >>> >>> It was a pleasure to clarify >>> >>
Received on Thursday, 29 October 2020 13:04:15 UTC