Yes—computers can be programmed to generate work that people judge creative. Whether that means a computer thinks creatively in the human sense is a separate, unsettled question. The answer depends on what counts as creativity, what is being evaluated, and who is doing the judging.
What does “thinking creatively” mean?
There is no universally accepted definition of creativity. A common practical test asks whether an idea or output is both new and valuable or effective. What counts as valuable depends on the task and audience: a useful solution, an expressive image, and an engaging piece of music call for different standards.
The OECD’s framework for assessing students in PISA 2022 defines creative thinking as “the competence to engage productively in the generation, evaluation and improvement of ideas that can result in original and effective solutions, advances in knowledge and impactful expressions of imagination.” That is a useful assessment framework, not a universal definition of creativity. OECD: Defining the construct for the PISA 2022 assessment.
In computational creativity research, a definition reported by Anna Jordanous describes the field as “the study and simulation, by computational means, of behaviour, natural and artificial, which would, if observed in humans, be deemed creative.” This definition focuses on observable behavior. It does not settle whether a computer has human-like understanding or agency. Jordanous, “A Standardised Procedure for Evaluating Creative Systems” (2012).
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What can computers do creatively?
Generative computer systems can produce candidate text, images, music, and other outputs. People can assess those results against criteria such as originality and effectiveness. That supports a measured conclusion: a system may perform creatively by some standards, without necessarily meeting every standard or thinking as a person does.
Fluency or novelty by itself is not enough. A result might sound polished yet be routine, or look unfamiliar without serving its purpose. The OECD’s AI capability framework treats generative abilities as matters for empirical assessment and notes that many generative systems struggle to produce surprising outputs. Its graded approach is a reminder that capability can vary by task and criterion. OECD AI Capability Indicators: Introducing the OECD AI Capability Indicators.
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A 2026 IJCAI paper proposes assessing creativity through newness, value, and surprise, and discusses applications to chess moves and paintings. It is a recent proposal, not a settled definition or proof that computers think like people. Yang and Tuzhilin, “Towards Defining, Measuring and Leveraging Creativity in AI Applications” (IJCAI 2026).
How should a computer’s creativity be judged?
A meaningful assessment first specifies what is under evaluation: the output, the process that produced it, the system’s ability to adapt, or collaboration between a person and a system. It should also identify the judges and criteria. Jordanous proposed the SPECS procedure to make evaluation standards explicit and systematic; an interdisciplinary tutorial surveys approaches across psychology, philosophy, cognitive science, and computer science. Jordanous (2012); Lamb, Brown, and Clarke, “Evaluating Computational Creativity: An Interdisciplinary Tutorial” (2018).
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- Novelty: Is the output new compared with a relevant baseline, rather than merely unfamiliar to one observer?
- Value or effectiveness: Does it meet the purpose of the task or audience?
- Surprise: Does it go beyond expected combinations or routine variation? Some frameworks emphasize this criterion; not all do.
- Domain and audience: Are the standards appropriate for the kind of work being assessed?
- Evaluation method: Are judgments made by people, formal measures, or a structured combination—and can the procedure be repeated?
No single score resolves every case. Different frameworks prioritize different criteria, so a claim that a system is “creative” is most informative when it says what was assessed and how.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Does creative output mean a computer thinks like a person?
No conclusion about human-like thought follows from creative-looking output alone. A system’s work can meet stated criteria for novelty and effectiveness while the broader questions of understanding, intention, and agency remain unanswered. The distinction matters: evaluating what a system produces is not the same as establishing what, if anything, it experiences or understands.
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So the most defensible answer is conditional: computers can be programmed to generate outputs that people judge creative under explicit criteria. Whether that amounts to “thinking creatively” depends on the definition being used and on evidence beyond the output itself.
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- Journal is appropriate for grades K-2. It contains 100 double-sided, primary ruled sheets that measure 7-1/2" x 9-3/4"
- Double-sided primary ruling is printed with solid and dotted lines. Ideal for beginning students who want to improve their handwriting
- Top half of each page is blank for illustrating stories. Cover includes a manuscript alphabet for reference
- Sewn binding is smooth, helps keep pages securely in place and lays flat when open
- Available in Blue
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