We’ll figure it out, eventually.
Yung Shin Van Der Sype and Wim Nauwelaerts of Alston & Bird write:
The European Data Protection Board (“EDPB”) has published draft guidelines on the concepts of controller and processor for public consultation. While its predecessor – the Article 29 Working Party – had issued guidance on the concepts of controller/processor (Opinion 1/2010, WP169 ) back in 2010, many practical concerns have been raised since the entry into force of the General Data Protection Regulation (“GDPR”). These concerns relate in particular to the substance and implications of the concept of joint controllership (in Article 26 GDPR) and the specific obligations imposed on processors (mainly in Article 28 GDPR). The new EDPB guidelines will replace the previous opinion of the Article 29 Working Party but are currently open for stakeholder feedback. Comments and suggestions on how to improve the guidelines can be provided to the EDPB by 19 October 2020 at the latest.
Read more on Privacy & Cybersecurity Blog.
You would need to read the output very carefully.
A New AI Model Focused on Doing, Not Thinking—and That’s Great News for Lawyers
From science fiction to computer science fact, artificial intelligence has come a long way, recently culminating with the unveiling with the third generation of the Generative Pretraining Transformer (GPT-3). Released by the famously connected OpenAI Foundation (think Elon Musk, Sam Altman, Mark Benioff and Peter Thiel), GPT-3 might be a game changer in legal and other knowledge-focused organizations.
It is different from other AI tools commonly used in business enterprises in two ways. First, it is a creation engine. AI tools are generally used in an enterprise to find or categorize information. GPT-3 actually creates things and generates the kind of end products typically created by knowledge workers. Second, it is pretrained. AI algorithms commonly need to be trained on large, proprietary datasets. You put a large number of samples through the engine, it recognizes patterns and can find documents with similar patterns or correlations. GPT-3 comes pretrained, on billions of substantive documents from purpose-built repositories such as CommonCrawl, Wikipedia and other public sources, which together comprise a significant portion of all expressed human knowledge. It’s functional out of the box, solving the primary challenge for business users.
… One criticism that has been levied on GPT-3 is that it does not “reason” as humans do, so on occasion its output is absurd. That’s an accurate criticism and the public conversation about GPT-3 is not short of humorous examples.
(Related)
https://www.theguardian.com/commentisfree/2020/sep/08/robot-wrote-this-article-gpt-3
A robot wrote this entire article. Are you scared yet, human?
We asked GPT-3, OpenAI’s powerful new language generator, to write an essay for us from scratch. The assignment? To convince us robots come in peace
For more about GPT-3 and how this essay was written and edited, please read our editor’s note below
Perspective. (Podcast) Using the library extension, https://www.libraryextension.com/?utm_source=libraryextension.com&utm_content=installed_extension&utm_medium=onpage_catalog_view I know that my local library already has 3 copies of this book
https://knowledge.wharton.upenn.edu/article/what-will-the-world-look-like-in-2030/
What Will the World Look Like in 2030?
Big demographic, economic and technological changes are coming — from an aging population in the U.S. and the rise of sub-Saharan Africa as a compelling middle-class market to automation causing “technological unemployment,” according to Wharton management professor Mauro Guillen.
In his new book, “2030: How Today’s Biggest Trends Will Collide and Reshape the Future of Everything,” Guillen discusses how these changes will affect us in the years to come. During a recent interview on the Wharton Business Daily show on SiriusXM, Guillen noted that while these trends have been gathering pace for years, the pandemic is accelerating many of them.
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