Topic

Artificial Intelligence

Fostering AI architects: a data strategy intern tells her story

As a Data Strategy Intern at idalab, Tina Emambakhsh explores how AI-/ML-based healthcare technology can be regulated in the future. Before joining idalab, Tina gained experience in a wide range of disciplines and sectors, having worked at the Austrian Embassy in Tehran, KPMG and Strategy&. Tina studied International Business Administration at WU Vienna and at Universidad del Pacífico, Peru, and is currently pursuing a master’s degree in International Economic Policy and Economics at SciencesPo and the Stockholm School of Economics. Her research interests lie at the interface between public policy and media.

idalab seminar #21: How TomTom is using AI to Create World-Class Maps and Traffic Services for Autonomous Driving

For over a decade TomTom has been creating consumer devices for navigation routing people from A to B as fast as possible. One of the key components in routing is the availability of a high-quality map.  While initially maps were being produced in a very laborious way involving a significant amount of manual work, map productization is nowadays becoming more and more automatized.

The future of AI may depend on historians and musicologists

The concept of “Artificial Intelligence” had a massive impact over the past several years. Marvelous tales about its prospective achievements abound, just as much as sceptical questions about whether (or when) the machines will finally substitute the humans on this planet. As a result of this heated discourse, leaders across many industries feel an urgent need to somehow incorporate AI technologies into their workflows, fearing to miss out on an important innovation step.

AI beyond pattern recognition #1: Interview with Christoph von der Malsburg

Today, the world seems enamoured  by the possibilities of Artificial Intelligence. As of now, this largely amounts to powerful, yet predictable and widely understood algorithms for search and pattern recognition, that inspired the era of Data Science and Machine Learning. While the effects of these techniques are undoubtedly great and in many use cases their potential has yet to be unlocked, their capabilities are far from human cognition:

Was kann KI – heute und morgen? – Interview mit Paul von Bünau für RETHINKING LAW

Professor Stephan Breidenbach und Dr. Paul von Bünau nähern sich in diesem Interview der Frage, was Künstliche Intelligenz heute im Kern ausmacht und was Voraussetzungen für echtes Verstehen wären. Darüber hinaus erörtern sie, welche Innovationen KI im Bereich der Rechtsdienstleistungen heute ermöglicht und welche Potenziale in Zukunft noch gehoben werden können.

idalab seminar #15: What makes an algorithm ethical? – Defining and implementing a Quality Criteria Catalogue for Algorithms

Algorithms are increasingly relied upon in decision making processes that can have far-reaching implications for all of us. They help doctors diagnose diseases and develop treatment plans. They tell police officers where to patrol. They decide who is going to be invited to the job interview. If these decisions are made by people and the way they decide seems harmful or unjust, our laws enable us to hold them accountable for their actions and correct them if necessary.

Die Sehnsucht nach Transparenz ist eine Sehnsucht nach Begründung. Warum Algorithmen lernen sollten, eine Geschichte zu erzählen.

Basis aller heutigen Künstlichen Intelligenz sind bekanntlich Algorithmen. Diese sind in den letzten Jahren in zunehmendem Ausmaß in den Fokus der öffentlichen Wahrnehmung gerückt. Dabei schwankt der Grad an thematischer Souveränität und Güte der einzelnen Wortmeldungen aus Presse, Politik und Gesellschaft teils erheblich.

idalab seminar #11: SELECT * FROM … natural language: databases, we need to talk!

Do you know the feeling? All you want is a break-down of last year’s sales numbers and suddenly you find yourself typing tedious heaps of SQL-statements, clicking through complicated dashboards or looking for the right number in an Excel sheet. The vast majority of decision makers has better things to do with their time. That’s why business intelligence software was originally born. But only 20% of users are actually coping with the solutions BI software provides. Instead, the BI team is spammed with ad hoc data requests. What if everyone had a personal virtual data analyst at hand?

Auf dem Weg zu einer nationalen KI-Strategie

Die Stiftung Neue Verantwortung hat jüngst eine Empfehlung für eine deutsche KI-Strategie in Form eines Diskussionspapiers herausgegeben. Hintergrund ist das Bestreben des Think Tanks, den gegenwärtigen Arbeitsprozess der Bundesregierung zum Thema KI-Strategie durch Experten-Input zu unterstützen und zu ergänzen. Paul von Bünau, Geschäftsführer der idalab GmbH, hat als einer der inhaltlichen Berater an dem Papier, das den Titel “Eckpunkte einer nationalen Strategie für Künstliche Intelligenz” trägt, mitgewirkt.