Monday, December 02, 2019


Explaining AI to GDPR regulators.
Companies could be fined if they fail to explain decisions made by AI
Businesses and other organisations could face multimillion-pound fines if they are unable to explain decisions made by artificial intelligence, under plans put forward by the UK’s data watchdog today.
The Information Commissioner’s Office (ICO) said its new guidance was vital because the UK is at a tipping point where many firms are using AI to inform decisions for the first time. This could include human resources departments using machine learning to shortlist job applicants based on analysis of their Cvs. The regulator says it is the first in the world to put forward rules on explaining choices taken by AI.
The guidance, which is out for consultation today, tells organisations how to communicate explanations to people in a form they will understand. Failure to do so could, in extreme cases, result in a fine of up to 4 per cent of a company’s global turnover, under the EU’s data protection law.
Not having enough money or time to explain AI decisions won’t be an acceptable excuse, says McDougall. “They have to be accountable for their actions. If they don’t have the resources to properly think through how they are going to use AI to make decisions, then they should be reflecting on whether they should be using it all.”


(Related)
Commission Expert Group report on liability for emerging digital technologies
On November 21, 2019, the European Commission’s Expert Group on Liability and New Technologies – New Technologies Formation (“NTF”) published its Report on Liability for Artificial Intelligence and other emerging technologies. The Commission tasked the NTF with establishing the extent to which liability frameworks in the EU will continue to operate effectively in relation to emerging digital technologies (including artificial intelligence, the internet of things, and distributed ledger technologies). This report presents the NTF’s findings and recommendations.




Spiderman’s bank?
WITH GREAT POWER COMES GREAT RESPONSIBILITY: ARTIFICIAL INTELLIGENCE IN BANKING
Arguably, no large financial institution can afford not to integrate AI into its business, but care should be taken to establish audit trails and make the parameters of AI deployment transparent and available for scrutiny. The opportunities AI offers to foster innovation and promote growth in the industry are significant but must be pursued responsibly in order to avoid serious harm.
The place of AI in financial institutions
In broad terms, the use of AI in financial institutions can be categorised into four groups. The first is in customer interactions and compliance, whether related to AML checks, fraud detection or personalised customer engagement. The second is in the context of financial systems and processes, such as payments[i] and treasury services. The third use is for the enhancement of financial products and the financial institution’s business model. This could involve faster loan-affordability checks, more personalised insurance premiums informed by policyholder behaviour or algorithmic trading in foreign-exchange markets. The final use case is to assist with regulatory reporting or change, including stress testing, ring-fencing in the United Kingdom or the transition away from LIBOR (London Interbank Offered Rate) as a reference rate.




For a variety of toolkits. Mr Zillman collects everything within his scope.
2020 Guide to Web Data Extractors
New on LLRX 2020 Guide to Web Data Extractors This guide by Marcus P. Zillman is a comprehensive listing of web data extractors, screen, web scraping and crawling sources and sites for the Internet and the Deep Web. These sources are useful for professionals who focus on competitive intelligence, business intelligence and analysis, knowledge management and research that requires collecting, reviewing, monitoring and tracking data, metadata and text.




For your browser collection.
Alternative search engine provides google results but with privacy
FastCompany – “Picture for a moment a version of Google Search that barely evolved from its early years. Instead of a results page cluttered by informational widgets, this one would primarily link out to other sites. And instead of tracking your search history for ad targeting purposes, this search engine would be decidedly impersonal. It turns out that such a thing exists today in Startpage, a Netherlands-based Google search alternative that emphasizes privacy. While it’s not the only privacy-first search engine—DuckDuckGo is a better-known example—Startpage is the only one whose search results come from Google, due to a unique and longstanding agreement in which Startpage pays the search giant to get a feed of links for any search. The result is a search engine that feels a lot like Google did before it leaned into personalized search and advertising and all of its requisite data collection—about 15 years ago…”



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