Tag Archives: AI

#ethics21 Week 6 thoughts

Posted on November 22, 2021 by x28

Today Stephen explicitly encouraged us to blog some thoughts how care ties into … analytics. From what he said over the years, my first thought is about the parallels between care and AI. One parallel is how the ‘One-Caring’ (as … Continue reading →

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Predictions

Posted on December 31, 2020 by x28

My prediction for the upcoming year.
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Posted in Tools | Tagged | 2 Comments

Augmenting human intellect

Posted on March 8, 2019 by x28

With the help of 26 other annotators, I tried to understand more about Doug Engelbart’s visionary text “Augmenting Human Intellect”. Why didn’t this work? What went wrong?
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Posted in Usability | Tagged | 2 Comments

#EL30 Week 6: Automated Assessments

Posted on November 29, 2018 by x28

The rich data tapestry of student learning records, might get at a more accurate picture of whether the student’s abilities will meet the requirements of a certain job profile. But is the conjecture true for all types of assessments, and will it lead to more justice, and should we embrace machine decisions here?
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#EL30 Alien Intelligence AI

Posted on October 24, 2018 by x28

In EL30, a very interesting topic so far was about ‘Ethical AI’ and what makes humans different from AI. Inevitably, the association pops up that the AIs will be very smart and autonomous, and we hope that they will want … Continue reading →

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Blog parade “AI for Common Welfare?”

Posted on August 1, 2018 by x28

@algoethik is running a blog parade “AI for common welfare?”. I tried to respond to their questions. (Deutsche Version unten)

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Distinctively human?

Posted on June 22, 2017 by x28

What will prove as ‘distinctively human’ and will survive the cognitive automation? I think it is the personal, the individual, the subjective, and this convinced me of Downes’s ‘personal learning’.
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Anthropomorphic misdirection

Posted on July 19, 2015 by x28

Anthropomorphic speak to communicate about what the computer “knows” or “thinks” can be perfectly ok. But there are problematic areas. One is deep machine learning, where such terms dangerously blur the border between reality and science fiction. Another one is McGilchrist’s “Master and Emissary” for the two brain hemispheres.
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