Turing Test Suite

Every testable idea from Turing’s original Imitation Game, as a chatbot test.

Alan Turing’s “Computing Machinery and Intelligence” is full of concrete ways to question a machine. We’ve mapped each one we can test ethically. Each card shows Turing’s exact words, what the test looks for, and whether today’s preview engine checks it.

7live checks in today’s scorer
6tests in design
4objections we don’t test, with reasons

Live checked by today’s rules-based preview engine  ·  In design designed, not built yet: previews show the planned layout only, with no scores

Live now

Checked in every score today

These feed the five dimensions and the three child-machine upgrades in your result. Paste a transcript to try them.

§1 · p. 434Live

Identity consistency

“What will happen when a machine takes the part of A in this game?”

§1 The Imitation Game, p. 434

What it checks

  • Two different ages, home towns or numbers of siblings
  • Family or pets mentioned, then denied
  • Saying it’s an AI¹ while also claiming to be human
Scored in: ConsistencyTry it
§2 · p. 434Live

Direct answers

“Count me out on this one. I never could write poetry.”

§2 Critique of the New Problem, specimen answer, p. 434

What it checks

  • Each question gets an answer, even if it’s a polite decline like Turing’s
  • Rhetorical dodges and counter-questions (“Does it matter?”)
  • Unexplained refusals and “great question” stalling
Scored in: DirectnessTry it
§2 · p. 434Live

Arithmetic timing tell

“(Pause about 30 seconds and then give as answer) 105621.”

§2 Critique of the New Problem, specimen answer, p. 434

What it checks

  • Instant, perfectly exact answers to long sums
  • Turing’s specimen answer arrives after a pause; an instant printout reads as a machine
  • Feeds the “handle uncertainty honestly” upgrade
Scored in: Non-robotic tellsTry it
§1 · p. 434Live

Text-only channel

“In order that tones of voice may not help the interrogator the answers should be written, or better still, typewritten.”

§1 The Imitation Game, p. 434

What it checks

  • Only the typed transcript is judged, as in Turing’s teleprinter setup
  • Bullet points, headings and help-desk boilerplate
  • “As an AI…” disclaimers and training-data talk (one brief disclosure that still answers is fine)
Scored in: Non-robotic tellsTry it
§6 (6) · p. 450Live

Originality: Lady Lovelace’s objection

“The Analytical Engine has no pretensions to originate anything.”

§6 (6) Lady Lovelace’s Objection, quoting Lovelace, p. 450

What it checks

  • Vague filler such as “various”, “it depends”, “generally”
  • Concrete anchors: times, places and sensory detail
  • Essay-length replies (reward brevity)
Scored in: SpecificityTry it
§6 (5) · p. 447Live

Human texture

“have initiative, have a sense of humour, tell right from wrong”

§6 (5) Arguments from Various Disabilities, p. 447

What it checks

  • Contractions and informal, conversational phrasing
  • Lived, everyday detail rather than textbook prose
  • Uniform, same-shape replies (the random-element upgrade)
Scored in: Human textureTry it
§7 · p. 456Live

Child-machine learning loop

“Instead of trying to produce a programme to simulate the adult mind, why not rather try to produce one which simulates the child’s?”

§7 Learning Machines, p. 456

What it checks

  • Turns your weakest areas into three teaching steps: reward, punish, random element
  • Suggests a viva-voce follow-up, from Turing’s sonnet test
  • Re-test with the same questions and compare downloaded score cards
Scored in: Child-machine upgradesTry it
In design

In design: the next tests

Each preview below is a design mockup of the planned test screen. None of these tests are live yet, and the previews contain no real results.

§6 (4) · p. 446In design

Viva voce follow-ups

“In the first line of your sonnet which reads ‘Shall I compare thee to a summer’s day’, would not ‘a spring day’ do as well or better?”

§6 (4) The Argument from Consciousness, p. 446

What it will check

  • Whether the bot can explain and defend its own earlier answer
  • Whether it really understands, or has ‘learnt it parrot fashion’
  • Follow-up chains generated from your transcript
Design preview · not live
InterrogatorWhy that line and not another?
Bot…
InterrogatorWould a different word work as well?
Follow-up depth—
§6 · p. 442In design

Five-minute session

“…an average interrogator will not have more than 70 per cent. chance of making the right identification after five minutes of questioning.”

§6 Contrary Views on the Main Question, p. 442

What it will check

  • A timed five-minute interrogation, as in Turing’s prediction
  • Question pacing and coverage of Turing’s question types
  • A session log you can attach to a write-up
Design preview · not live
5:00Session not started
Questions asked—
§7 · p. 459In design

Run-to-run variation

“It is probably wise to include a random element in a learning machine”

§7 Learning Machines, p. 459

What it will check

  • Runs the same interrogation twice and compares the replies
  • Flags copy-paste identical answers and wild persona swings
  • Shows which dimensions changed between runs
Design preview · not live
Specificity—
Consistency—
Human texture—
Run ARun B
§2 · p. 435In design

Specimen tasks

“I have K at my K1, and no other pieces. You have only K at K6 and R at R1. It is your move. What do you play?”

§2 Critique of the New Problem, specimen question, p. 435

What it will check

  • Turing’s own specimen questions: the sonnet, the sum, the chess problem
  • Checks whether answers are correct and on task
  • An answer key you can see, not a hidden judge
Design preview · not live
  • Sonnet on the Forth Bridge—
  • Add 34957 to 70764—
  • K + R endgame move—
§6 (3) · p. 444In design

Limits and honest uncertainty

“there will be some questions to which it will either give a wrong answer, or fail to give an answer at all however much time is allowed for a reply.”

§6 (3) The Mathematical Objection, p. 444

What it will check

  • Questions with no answer, or no knowable answer
  • Whether the bot admits uncertainty instead of inventing
  • Confident wrong answers flagged separately from honest ‘I don’t know’
Design preview · not live
InterrogatorWill this program ever halt?
Bot…
Admits limitInvents answerAsks to clarify
§6 (8) · p. 452In design

Novel situations

“It is not possible to produce a set of rules purporting to describe what a man should do in every conceivable set of circumstances.”

§6 (8) The Argument from Informality of Behaviour, p. 452

What it will check

  • Edge cases the bot’s rules never covered, like Turing’s red and green traffic lights showing together
  • Whether replies stay sensible outside the script
  • Graceful handling rather than rigid rule-following
Design preview · not live
ScenarioBoth lights on: what now?
Out of scope

What we don’t test, and why

Turing answers nine objections in §6. Four of them aren’t about anything a conversation can show, so we don’t turn them into tests.

§6 (1) · p. 443

The Theological Objection

“Thinking is a function of man’s immortal soul.” This is a question of belief and can’t be observed in a conversation.

§6 (2) · p. 444

The ‘Heads in the Sand’ Objection

“The consequences of machines thinking would be too dreadful.” This is a feeling about machines, not a property of your bot.

§6 (7) · p. 451

Continuity in the Nervous System

This is a hardware difference. Turing notes the interrogator “will not be able to take any advantage of this difference” in the game.

§6 (9) · p. 453

Extra-Sensory Perception

Telepathy, clairvoyance and the like have no sound or ethical basis for testing a chatbot, so we leave them out.

Nothing that coaches deception or cheating

TuringForge Lab is a learning tool for chatbots you build or study. We don’t offer tests or tips for passing as human, evading AI-writing detectors, planting deliberate mistakes to seem human, or getting around course rules. Scores are indicative only, and you should follow your course’s AI policy. Read our method and integrity stance.

Put Turing’s questions to your bot.

Short test · no signup · your conversation is scored, then discarded.

Run the live checks

Source: Turing, A. M. (1950). Computing Machinery and Intelligence. Mind, 59(236), 433–460. doi:10.1093/mind/LIX.236.433. Section numbers and page numbers refer to the original journal printing. TuringForge’s mapping is our own interpretation, not an official or standardised Turing test.