Moving up the Knowledge Work Value Chain
Interesting AI supported knowledge work workflow based on a simple model for knowledge work where the emphasis is on improving the quality of the input and not on speeding up the processing part.
Interesting AI supported knowledge work workflow based on a simple model for knowledge work where the emphasis is on improving the quality of the input and not on speeding up the processing part.
Hand on heart: How often when you use the convenience of an AI do you think about the enormous effort behind it?
The AI Anatomy Map is an exploded view diagram that combines and visualizes three central, extractive processes that are required to run a large-scale artificial intelligence system: material resources, human labor, and data using Amazon’s Echo as example. It is worth a deep dive:
Go to the original website to see the picture in full scale.
Ich möchte gerne den Podcast Mit Herz und KI des DUP Magazins empfehlen, z. B. die sehr hörenswerte Folge Patriarchat.exe läuft im Hintergrund – warum KI schockierend sexistisch ist:
Redakteurin Fanny Rosenberg spricht mit Eva Gengler, einer der führenden Stimmen für faire Algorithmen. Gemeinsam gehen sie der Frage nach, ob mit KI gerade eine Zukunft programmiert wird, die eigentlich längst Vergangenheit sein sollte. Doch warum kommen KI-Technologien überhaupt als digitaler Chauvinist daher? Wie können wir diese maschinelle Diskriminierung erkennen? Und wie können wir uns von diesen tiefsitzenden Vorurteilen von KI-Systemen lösen?
Die letzte Live Session unseres letzten Wissensmanagement-MOOC ist nun auch online: Prof.in (FH) Mag.a (FH) Barbara Geyer, PhD von der Hochschule Burgenland nimmt uns mit und gibt Einblick, wie sie persönlich KI-Tools als Unterstützung ihrer Arbeit, auch der wissenschaftlichen Arbeit nutzt.
Vielleicht diejenige Live Session die mein eigenes Arbeiten am konkretesten und praktischsten beeinflusst hat. Vielen Dank, Barbara! Und euch viel Spaß (Dauer 49’44 Min)
Last week I attended a really inspiring talk held by Patrick Cohendet (HEC Montreal), organized by the Research Network of the KMGN: Knowledge Based Approaches to The Firm: An Idea-Driven Perspective.
What I really liked and what was an excellent food for thought was the conception of Knowledge Management as a bridging funtion between the Generating of (many) Ideas and the Innovation Management. Knowledge Management facilitates the evaluation and filtering of ideas by ensuring that during this process relevant knowledge is available and efficiently used:
„[…] an idea needs to be equipped with various bodies of knowledge in order to become commercially viable. After the initial spark, the “social and cognitive construction of the idea” phase becomes crucial in the ideation journey. The goal is to provide the idea with enough knowledge to form an internally consistent set of concepts and ultimately make it commercially viable.“ (Patrick Cohendet)
So, the question is not – as often asked for in organizations – to clearly distinguish between KM on the one and Innovation Management on the other side. On the contrary, KM is at the very basis and an essential prerequisite for a successful Innovation Management, isn’t it? Always felt, now well explained. Thank you, Patrick!