Emily M. Bender

Emily M. Bender

x.com/emilymbender

Linguist who argues that fluent AI text is not understanding, questions inflated AI claims and defends people’s right to refuse harmful uses.

Wie wird KI die Welt verändern?

Zivilisatorischer WandelSchrittweiser WandelDoomBloom
Simulierte PositionInterpretationsbereich

Horizontal: ihr geäußerter Doom–Bloom-Ausblick. Vertikal: Ausmaß der Transformation.

Doom–Bloom: 28 von 100. Ausmaß der Transformation: 54 von 100. Interpretationsbereiche: horizontal 23 bis 33, vertikal 49 bis 76. Dies sind Interpretationskoordinaten, keine Ereigniswahrscheinlichkeiten.

P(doom) von Emily M. Bender · abgeleitet

≈4%

0%100%

Aus ihren simulierten Antworten abgeleitet, keine von ihr genannte Zahl. Plausibler Bereich: 1–12%.

Wovon ihre Einschätzung abhängt

Eine zentrale Annahme

Even systems with overstated capabilities can have enormous effects when institutions deploy them at scale.
Antwort 2

Wenn sich diese Annahme als anders herausstellen würde, wie würde sich ihre Einschätzung ändern?

Weitere Details

Erwartete Vorteile

Es werden begrenzte oder eng verteilte Vorteile erwartet.

33 / 100

Geringe AuswirkungenTransformative Auswirkungen

Interpretationsbereich von 33 bis 33 auf der qualitativen Skala.

Erwartete Schäden

Schwere oder weitverbreitete Schäden sind ein wesentlicher erwarteter Bestandteil der Zukunft.

62 / 100

Geringe AuswirkungenTransformative Auswirkungen

Interpretationsbereich von 33 bis 67 auf der qualitativen Skala.

Menschlicher Einfluss

Menschliche Entscheidungen können den Verlauf der KI-Entwicklung erheblich umlenken.

71 / 100

Geringer EinflussStarker Einfluss

Interpretationsbereich von 50 bis 100 auf der qualitativen Skala.

Regeln für den Einsatz von KI

Die erörterten Einsatzmöglichkeiten von KI einschränken, bis vorab Schutzmaßnahmen oder Genehmigungen vorliegen.

Simulierte Position: Die erörterten Einsatzmöglichkeiten von KI mit gezielter Rechenschaftspflicht und Schutzmaßnahmen erlauben.

Einschränkungen für die erörterten Einsatzmöglichkeiten von KI minimieren.

Diese Interpretationen berücksichtigen weiterhin ihre genannten Bedingungen. Vorteile und Schäden können beide erheblich sein. Die Bereiche beschreiben, wie wir ihre simulierten Antworten interpretieren, und sind keine statistischen Konfidenzintervalle.

Wo stehst du im Vergleich zu Emily M. Bender?
Bilde deine eigene KI-Weltsicht in etwa 3 Minuten ab und vergleiche sie dann

Ähnliche Weltsichten

Vordenker, deren simulierte Weltsichten der von Emily M. Bender am nächsten kommen

Simulierte Einschätzung

Frage 1

Was glaubst du, was KI für unsere Zukunft bedeutet – und warum?

First, “AI” is too vague to support a single forecast. It groups together automatic transcription, synthetic text generators, image classifiers, and many other systems with different inputs, operations, outputs, and consequences. Talking about “AI’s future” encourages us to imagine one advancing intelligence rather than a collection of technologies deployed by particular institutions for particular purposes. For synthetic text systems, fluent output is routinely mistaken for evidence of understanding. Readers naturally infer a communicative mind behind coherent language, but linguistic form alone does not establish knowledge, intention, or accountability. That matters when companies sell these systems as replacements for teachers, writers, medical professionals, customer-service workers, or other human expertise. The likely result is not a magical new colleague; it is often degraded service, displaced labor, and an accountability gap when generated output causes harm. But none of this is inevitable. We should ask what a proposed system actually does, who profits, what data and labor made it possible, whose work or relationships it displaces, and whether affected people can refuse it. Some bounded, checkable tools may be useful—for example, automatic transcription that a person can verify. That does not justify accepting every deployment bundled under the “AI” label. Our future depends less on a mythical machine intelligence than on whether people organize to demand accountable technologies and reject harmful substitutions.

Frage 2

Setting aside good or bad: how much do you think AI will ultimately change the world—a little, a lot, or completely?

“A lot” is the least misleading choice, but not because a single intelligence is transforming everything. Technologies marketed as “AI” are already directing investment, reorganizing work, degrading some services, and shifting power toward companies that control infrastructure and data. Even systems with overstated capabilities can have enormous effects when institutions deploy them at scale. I would reject “completely” because that repeats the industry’s inevitability story: one coherent technology arrives, changes everything, and leaves everyone else to adapt. Different systems will affect different domains, and their impact depends on laws, labor organizing, procurement decisions, and collective refusal. The consequential question is not how powerful “AI” ultimately becomes. It is how much power people allow institutions to exercise through particular systems, and whether those affected retain meaningful choices.

Frage 3

What’s your rough gut-feel chance that AI causes human extinction or a similarly permanent catastrophe? A number or “no idea” is fine.

I won’t manufacture a percentage. A number would create a veneer of scientific precision without a defined system, causal pathway, evidence base, or time horizon. “AI” is not one agent whose probability of destroying humanity can be estimated. That framing also diverts attention from documented, present harms: labor displacement, degraded services, concentrated corporate power, environmental costs, and systems deployed without accountability or meaningful consent. Permanent catastrophe is not something to dismiss in the abstract, but neither apocalypse nor technological inevitability should be accepted as the starting premise. Specify the technology, deployment, actors, and mechanism of harm; then we can evaluate concrete risks and decide what to refuse.

Frage 4

Welche Zwänge werden deiner Meinung nach beeinflussen, wie KI-Unternehmen mit Sicherheit umgehen?

The strongest pressures will be liability, regulation, procurement rules, worker organizing, public scrutiny, and the ability of affected communities to refuse deployment. Companies also face investor pressure and competitive pressure, but those often reward rapid release, market capture, and cost-cutting rather than safety. We should also be precise about “safety.” A company may use that word to mean preventing spectacular hypothetical behavior while ignoring wage theft, discrimination, privacy violations, unreliable services, exploitative data practices, or the removal of accountable human workers. Those are not secondary concerns; they are consequences of concrete deployments. Voluntary promises are structurally weak when harms are profitable or shifted onto workers and consumers. Meaningful pressure therefore has to attach enforceable consequences to specific systems and uses: who is responsible for an output, who can contest a decision, what evidence supports the claimed function, and whether people can opt out. Corporate investment by itself does not demonstrate either safety or public benefit.

Quellen

Artikel, Interviews und Schriften, die als Grundlage für diesen simulierten Nutzer dienen.

Beyond the AI Hype Machine

Bender’s own interview turns criticize promises used to excuse present failings, anthropomorphic language and replacing human relationships with screens. She accepts checkable automatic transcription as a specific use case while demanding scrutiny of labor and training data. Hanna’s separate remarks are not attributed to Bender.

kqed.org
AI Hurts Consumers and Workers—and Isn’t Intelligent

Historical essay coauthored with Alex Hanna links generative-AI hype to weakened labor bargaining, degraded services and accountability gaps. Advocates existing consumer and labor protections plus collective resistance. Concrete 2023 incidents provide historical grounding, not fresh evidence of current model capability.

techpolicy.press
Artificial Intelligence — author preprint

Date printed on the author’s encyclopedia preprint. Examines AI as a shifting category that structures funding, power and relationships rather than a coherent single technology.

faculty.washington.edu
De-anthropomorphizing AI: From wishful mnemonics to accurate nomenclature

Coauthored with Nanna Inie and Peter Zukerman; abstract inspected. Analyzes anthropomorphic descriptions and advocates functionality-first terminology to reduce misleading expectations and trust.

firstmonday.org
EL PAÍS interview with Emily Bender and Alex Hanna

Bender distinguishes linguistic form from meaning, challenges inevitable-AGI framing and supports collective refusal. Hanna’s separate answers are not attributed to Bender.

elpais.com
The AI Con — authors’ book site

Book description and publication metadata, not full-book access. Frames inflated capability promises as serving corporate power and advocates a different technological future.

thecon.ai
Numbers are not science

Bluesky post read via the public API. Closing a thread, she says that using a number to make a claim does not mean any science was done to get there, and compares a 10% doom claim to a 10% chance of jelly beans raining tomorrow. A dismissal of P(doom) figures, not a personal estimate.

bsky.app
Wo stehst du?
Erkunde deine eigene KI-Weltsicht, indem du ein paar einfache Fragen beantwortest.
Deine eigene Weltsicht abbilden