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Moral Codes

Designing Alternatives to AI
Authors: Blackwell, Alan F.;
Abstract

Why the world needs less AI and better programming languages. Decades ago, we believed that robots and computers would take over all the boring jobs and drudgery, leaving humans to a life of leisure. This hasn't happened. Instead, humans are still doing boring jobs, and even worse, AI researchers have built technology that is creative, self-aware, and emotional—doing the tasks humans were supposed to enjoy. How did we get here? In Moral Codes, Alan Blackwell argues that there is a fundamental flaw in the research agenda of AI. What humanity needs, Blackwell argues, is better ways to tell computers what we want them to do, with new and better programming languages: More Open Representations, Access to Learning, and Control Over Digital Expression, in other words, MORAL CODE. Blackwell draws on his deep experiences as a programming language designer—which he has been doing since 1983—to unpack fundamental principles of interaction design and explain their technical relationship to ideas of creativity and fairness. Taking aim at software that constrains our conversations with strict word counts or infantilizes human interaction with likes and emojis, Blackwell shows how to design software that is better—not more efficient or more profitable, but better for society and better for all people. Covering recent research and the latest smart tools, Blackwell offers rich design principles for a better kind of software—and a better kind of world.

Keywords

thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning, thema EDItEUR::U Computing and Information Technology::UY Computer science::UYZ Human–computer interaction, Intelligent User Interfaces, Program synthesis, Explainability, Smart Tools, Human-Computer Interaction, Neurosymbolic systems, Human-Centered AI, End-User Programming, Ethical AI, Trust and transparency, AI and creativity, interactive AI, visualization

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    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    11
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
11
Top 10%
Average
Top 10%
Green
hybrid
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