The Nine Objections

In the second half of his 1950 paper, Turing systematically addresses nine major objections to the possibility of machine intelligence. His responses demonstrate remarkable prescience, anticipating many contemporary debates in AI and philosophy of mind.

"I do not wish to give the impression that I think there is no mystery about consciousness. There is, for instance, something of a paradox connected with any attempt to localise it. But I do not think these mysteries necessarily need to be solved before we can answer the question with which we are concerned in this paper."

Alan Turing, on the Argument from Consciousness

The Systematic Analysis

1

The Theological Objection

The Objection:

Thinking is a function of the immortal soul. God has given souls only to humans and animals, not to machines. Therefore, machines cannot think.

Turing's Response:

This objection implies serious restrictions on God's omnipotence. If God chose to bestow souls on machines, who are we to say this is impossible? The theological argument provides no evidence that God opposes machine intelligence.

Modern Relevance: Contemporary discussions of AI consciousness and personhood echo these theological concerns, particularly in debates about AI rights and moral status.
2

The "Heads in the Sand" Objection

The Objection:

The consequences of machines thinking would be too dreadful. Humans would lose their superior status and potentially face domination or extinction by machines.

Turing's Response:

This expresses fears about consequences rather than providing arguments against possibility. Emotional discomfort doesn't constitute evidence that thinking machines cannot exist.

Modern Relevance: This anticipates contemporary concerns about AI safety, job displacement, and existential risk from superintelligent AI systems.
3

The Mathematical Objection

The Objection:

Based on Gödel's incompleteness theorem, there are fundamental limitations to what any digital computer can prove or determine. These limitations might distinguish machines from human intelligence.

Turing's Response:

Humans are likely subject to similar mathematical limitations. Constructing questions to exploit these limitations would require detailed knowledge of the machine's programming - unavailable to interrogators.

Modern Relevance: The Lucas-Penrose argument continues debate, though its practical relevance to AI capabilities remains questionable.
4

The Argument from Consciousness

The Objection:

Only through introspection can we know that thinking occurs. A machine might simulate intelligent behavior without genuine inner experience or consciousness.

Turing's Response:

This leads to solipsism - if direct introspective access is required, we could never know that other humans think either. We should apply the same evidential standards to machines as to other people.

Modern Relevance: This remains the most contentious objection, directly relevant to debates about AI consciousness and whether LLMs truly "understand" language.
5

Arguments from Various Disabilities

The Objection:

Machines can never be kind, resourceful, creative, have humor, tell right from wrong, fall in love, enjoy aesthetic experiences, learn from experience, or use words properly.

Turing's Response:

Many claims are based on limited experience with primitive machines. Some abilities seem arbitrarily human-specific - why should universal intelligence require precisely human sensory preferences?

Modern Relevance: Contemporary AI systems have demonstrated many previously "impossible" capabilities: creativity, humor, learning, and sophisticated language use.
6

Lady Lovelace's Objection

The Objection:

Machines can only follow programmed instructions and cannot originate anything genuinely new or creative. They can do only "whatever we know how to order them to perform."

Turing's Response:

Machines frequently surprise their programmers. Even in a deterministic universe, events can be surprising and seem "new." Learning machines can develop beyond their initial programming unpredictably.

Modern Relevance: Modern AI demonstrates remarkable creativity and emergent behaviors unpredictable from training data alone, challenging traditional notions of machine originality.

Analytical Insights

Methodological Patterns

Turing's responses reveal several consistent strategies: rejecting anthropocentric bias (why should intelligence require human-specific traits?), demanding evidential consistency (apply the same standards to humans and machines), and distinguishing between practical limitations and fundamental impossibilities.

Contemporary Relevance

Many objections persist in modern AI debates, particularly consciousness and creativity arguments. However, recent advances in large language models and neural networks have demonstrated capabilities once thought uniquely human, validating several of Turing's predictions.

Philosophical Sophistication

The objections and responses engage fundamental questions in philosophy of mind: the nature of consciousness, the relationship between behavior and mental states, the possibility of other minds, and the criteria for intelligence attribution.