Thursday, March 16, 2017, 2:30 pm
Title: 5000 Years: Tax, Technology & Analytics
Speaker: Dr. Dirk Tassilo Hettich, Senior Consultant Tax Technology & Analytics
Bio: After having researched brain-computer interfacing for communication and control for almost 10 years, Dirk decided it is time to see how big data and advanced analytics do apply in an economic context and joined the Tax Techology & Analytics team at EY Stuttgart led by Florian Buschbacher in March of 2016. Since then he has applied his software development, machine learning, and visualization expertise in multiple client projects and is still amazed by all the real-world potential of artificial intelligence.
Abstract: New tools for new requirements in tax – from paper, calculators, and spreadsheets towards real-time tax including advanced analytics and machine learning. Digital transformation is happening in all aspects of a company and taxation intersects with almost all such aspects. The Tax Technology & Analytics team resolves complexity by applying state-of-the-art software development, database, and analytics technologies on a daily basis. This talk aims at giving insights to where big data and advanced analytics do apply in the supposedly dusty topic of taxation including working examples.
Time and Location: Thursday, March 16, 2017, 2:30 pm, Big Data Lab Frankfurt at the Chair for Databases and Information Systems (DBIS), Goethe-University Frankfurt.
Thursday, March 9, 2017, 1:45 pm
Title: MariaDB, MySQL and Four Decades of RDBMS Theory and Practice
Speaker: Kaj Arnö, Chief Evangelist at MariaDB Corporation
Bio: Software industry generalist, having serving as VP Professional Services, VP Engineering, CIO and VP Community Relations of MySQL AB prior to the acquisition by Sun. At Sun, served as MySQL Ambassador to Sun and Sun VP of Database Community. Board member of Carus Ltd Ab (Åland) and Footbalance Systems Oy (Helsinki, Finland). Past founder, CEO and 14 year main entrepreneur of Polycon Ab (Finland). Founder of what is now MariaDB Corporation Ab in 2010. Founded Green Elk (Outdoors Community) 2014. Now serving as Chief Evangelist of MariaDB Corporation.
Abstract: Plus ça change, plus c’est la même chose: Using databases require developers to be able to combine theory and practice in a way that has changed its form surprisingly little since the 1980s. Underlying themes have remained and seem cyclic. Central control moves to decentralised and back to central; memory constraint get relieved, only to again take effect in microservices. Complex pre-relational structures get a revival in in NoSQL, only to go back to relational again. Kaj Arnö takes an architectural look at RDBMSes spanning the times he’s been exposed to databases, since early 1980s.
Time and Location: Thursday, March 9, 2017, 1:45 pm, Big Data Lab Frankfurt at the Chair for Databases and Information Systems (DBIS), Goethe-University Frankfurt.
Thursday, February 9, 2017, 2:45 pm at the 7 Konferenz für Sozial-und Wirtschaftdaten in Berlin, organised by RatSWD.
Title: Big Data and The Great A.I. Awakening.
Speaker: Prof. Roberto V. Zicari, Frankfurt Big Data Lab, (Johann Wolfgang Goethe-Universität Frankfurt am Main)
Companies with big data pools can have great economic power. Today, that shortlist includes Google, Microsoft, Facebook, Amazon, Apple and Baidu.
I think we’re just beginning to understand the implications of data as an economic asset.
Steve Lohr (a journalists from The New York Times) had a recent conversation with Andrew Ng, a Stanford professor who worked at Google X, co-founder of Coursera and now chief scientist at Baidu. He asked him why Baidu, and he replied there were only a few places to go to be a leader in A.I. Superior software algorithms, he explained, may give you an advantage for months, but probably no more. Instead, Ng said, you look for companies with two things — lots of capital and lots of data. “No one can replicate your data,” he said. “It’s the defensible barrier, not algorithms.”
I asked myself the following question: Technology is moving beyond increasing the odds of making a sale, to being used in higher-stakes decisions like medical diagnosis, loan approvals, hiring and crime prevention. What are the societal implications of this?
steve Lohr argues that the new decisions that data science and AI tools are increasingly being used to make — or assist in making — are fundamentally different than marketing and advertising. In marketing and advertising, a decision that is better on average is plenty good enough. You’ve increased sales and made more money.
But the other decisions are practically and ethically very different. These are crucial decisions about individual people’s lives. For these kinds of decisions, issues of accuracy, fairness and discrimination come into play.
What we probably need is some sort of auditing tool; the technology has to be able to explain itself, to explain how a data-driven algorithm came to the decision or recommendation that it did. And it would important that a “human remains in the loop” for most of these kinds of decisions for the foreseeable future.
Time and Location: February 9, 2:45 pm at the 7 Konferenz für Sozial-und Wirtschaftdaten in Berlin, organised by RatSWD (Rat für Sozial-und Wirtschaftdaten: https://www.ratswd.de )
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