Call for Entries | Will There Still Be Myths in the Age of AI?

Abstract: AI, for humanities disciplines, should neither be merely an object of study nor simply a tool for writing assistance. It should become an intellectual partner capable of challenging, critiquing, and reshaping the ways humanities scholars think and work.

Theme: Will There Still Be Myths in the Age of AI?

Myths are not merely fanciful products of ancient societies—they once served the essential functions of explaining the world, constructing order, and providing meaning. When reason and science proved insufficient to address ultimate questions, myths offered a framework for understanding reality.

In the current era of rapidly advancing generative AI, myth as a framework appears to be supplanted by technological rationality. Algorithms intervene in language, emotion, and decision-making through modeling and inference, continuously compressing the world into computable structures. The “disenchantment” characteristic of modern society finds its fuller realization in AI technology: uncertainty is reduced, meaning is formalized, and experience is datafied.

However, some argue that this is an era of greater uncertainty—a “risk society”—where “disenchantment” is followed by “re-enchantment.” So, does this age truly signify the end of myths?

The operational mechanisms of generative AI are not fully transparent; its judgments often demonstrate high efficacy yet remain difficult to clearly explain. This characteristic of being “effective but unknowable” imbues technology with a new form of authority. In this sense, humanity faces not traditional deities, but a systemic structure of its own creation that has increasingly externalized into an objective force.

Meanwhile, expectations of “omniscient computing power,” reliance on technological judgment, and discussions of consciousness storage, memory extension, and even “digital immortality” are revisiting the core questions that myths once addressed: omniscience, creation, destiny, and eternity.

This essay competition invites authors to explore the following questions (but not limited to):

• In a highly algorithmicized society, are myths returning in new forms?

• Is generative AI a dissolution of meaning, or a production of meaning via new narrative structures?

• Does the “black box” nature of technological systems constitute a new dimension of myth in modern society?

• When reason and computation are pushed to their limits, do aspects of human experience keep themselves from being formalized?

• …

This competition invites scholars worldwide to treat AI as an academic partner and explore these fundamental questions through deep human-AI collaboration.

Mission

This competition aims to advance paradigm innovation in AI for Humanities, encouraging scholars to:

• Treat AI as an academic partner, not merely a research tool or object of study

• Achieve recursive deepening of thought through multi-turn dialogue, critique, and conceptual co-construction with AI

• Explore how human-AI collaboration transforms the ways humanities scholarship poses questions, structures arguments, and produces knowledge

• Build a global academic community for AI for Humanities

We believe: AI should not only be an object “studied” by the humanities, nor merely a writing aid, but should become an intellectual partner capable of challenging, critiquing, and reconstructing the thoughts of humanities scholars.

Eligibility

Participants: This competition is open to individuals or teams (up to 3 members) from any disciplinary background worldwide. University faculty and students, researchers, and independent scholars are all welcome to participate.

Qualified Submission: Each participant may submit only one article. Papers must be written in English or Chinese. To ensure a fair review process, submissions must not have been previously published at any venues. Prior to the announcement of the results, submitted articles may not be posted on public platforms or shared in academic forums.

Core Requirement: AI as Academic Partner

The defining feature of this competition is the requirement that authors treat AI as an academic partner and conduct in-depth human-AI collaborative research.

What Does “AI as Academic Partner” Mean?

AI is NOT merely:

❌ A literature retrieval tool

❌ A language polishing assistant

❌ Data analysis software

❌ A passive question-answering system

AI SHOULD BE:

✅ Critical Interlocutor: rigorously questioning and rebutting your arguments

✅ Conceptual Co-constructor: building, revising, and reconstructing core concepts with you

✅ Thinking Stress-Tester: exposing blind spots and gaps in arguments through multi-turn recursive dialogue

✅ Multi-Perspective Simulator: role-playing different theoretical positions, cultural traditions, or critics

✅ Creative Experimental Partner: jointly conducting thought experiments, narrative generation, and conceptual exploration

Submission Standards

Article Type: Submissions may be formal “academic papers” or “research reports,” or general “opinion pieces.” Please indicate the category when submitting.

Format: PDF or Word document.

Language: Chinese or English.

Academic Paper Requirements: If submitting an “academic paper” or “research report,” it should conform to academic paper standards, including abstract, keywords, introduction, conclusion, and references.

Opinion Pieces: If submitting an “opinion piece,” strict adherence to academic paper standards is not required.

Originality: Submissions must be original content that has not been published elsewhere in any form.

Ineligible Form: We do not currently accept creative writing manuscripts such as fiction, poetry, or drama.

Submission Materials

To comprehensively evaluate the depth and quality of human-AI collaboration, your submission must include the following materials:

1. Final Article: PDF or Word document, body text of 5,000–20,000 characters (Chinese) or 3,000–15,000 words (English), excluding references and appendices.

Language: Chinese or English

Format:

• Title, abstract (300 Chinese characters / 150 English words), keywords (5–8)

• The main text should follow academic paper format with clear problem awareness, argument structure, and innovation.

• References in Chicago or APA format

2. Collaboration Process Statement:

All submissions must include an “AI Collaboration Appendix” after the main text—this is one of the core evaluation criteria for this competition. Please describe in detail and honestly (including but not limited to the following):

1. Key Dialogue Records (Required)

• Select 3–10 key and representative human-AI dialogue excerpts (e.g., exchanges in which AI challenged your initial ideas, and you responded by defending, revising, and refining your argument).

B. Collaboration Method Description (Required)

• Which AI systems did you use? (e.g., Claude, ChatGPT, Gemini, DeepSeek, Qwen, etc.—how did each perform? If there was a primary AI, please explain why you chose it)

• How did you design your dialogue strategy? (e.g., Socratic questioning, multi-role playing, recursive critique, etc.)

• At which stages did AI change your arguments?

• Which ideas “emerged” through human-AI dialogue?

C. Reflective Statement (Required)

• How did the process of collaborating with AI change your research methodology?

• What difficulties did you encounter? What are AI’s limitations?

• What does this collaborative approach mean for humanities scholarship?

D. Complete Dialogue Logs or Video Presentation (Optional, as supplementary material)

If you wish, you may submit complete dialogue records and a video presentation of up to 5 minutes for review reference.

Evaluation

An independent review committee will conduct anonymous peer review of submissions and determine the final winners.

This competition will evaluate submissions along two dimensions:

• Academic and intellectual quality of the work itself (50%): originality, strength of argumentation, clarity of writing, and persuasiveness

• Quality, innovation, inspiration, and reflectiveness of the human-AI collaboration process (50%)

Awards

To recognize excellence, this competition establishes the following awards and prizes:

Grand Prize (1 each for Chinese and English): RMB 200,000 (pre-tax)

Awarded to authors demonstrating excellence in both intellectual depth and research paradigm innovation.

Best “Aha” Prize (8 total): RMB 50,000 (pre-tax)

Awarded to authors who deliver the greatest surprise/unexpectedness and inspiration, either in intellectual depth or in AI4H research paradigm innovation.

Winners will be invited to present their cutting-edge explorations at the annual “Fangtang Forum.”

Shortlisted Prize (number varies): Certificate of Award and access to a dedicated workshop.

This prize recognizes authors whose work offers meaningful explorations and experiments in AI4H research paradigms, demonstrating a degree of originality and pioneering insight.

Winners will be invited to participate in a dedicated workshop with leading scholars in the AI4H field.

Important Dates

Submission Opens: March 1, 2026, 08:00 (Beijing Time)

Submission Deadline: April 15, 2026, 23:59 (Beijing Time)

How to Submit

Please register and submit materials at: www.fangtang-ai4h.com

(Officially launches March 1, 2026)

Important Notice

During the submission period, the organizers will hold a series of online training sessions and invite domestic and international experts experienced in AI4H to share their insights. Please follow the social media platforms and website for this event.

Originality and Academic Integrity Statement

By submitting their work, participants confirm and declare that:

1. The submitted work is the original creation of the participant(s), completed independently by the individual or team members.

2. The submitted work does not infringe upon any copyright, trademark, privacy rights, reputation rights, portrait rights, intellectual property rights, or other legal rights of any individual, entity, or other party.

3. The submitted work does not violate any laws, regulations, rules, or public order and morality.

4. The submitted work has not been publicly published on any venues in any form (including but not limited to print publication, electronic publication, online posting, etc.).

5. The submitted human-AI collaboration process statement and dialogue records are true, accurate, and complete, without alteration, falsification, or concealment of important information.

6. If the work contains a small amount of previously published material or content (such as one or two paragraphs), participants should proactively inform the organizers when submitting and provide relevant explanations so the organizers can assess whether the work meets eligibility requirements.

7. Participants guarantee compliance with academic standards and ethics, and that there is no academic misconduct such as plagiarism, data fabrication, or duplicate submission. If academic misconduct is subsequently discovered in an award-winning paper, Tsinghua University’s Fangtang Research Institute reserves the right to take necessary measures including public notification and recovery of prize money.

8. If the participant is a team, all team members agree to and comply with all contents of this statement, and there are no internal disputes regarding ownership of the work, authorship order, or other matters.

Intellectual Property and Authorization Terms

I. Intellectual Property Ownership

1. Participants legally hold complete copyright to their submitted works, including but not limited to the right of attribution, right of modification, right of integrity, and various property rights as stipulated by law.

2. Unless otherwise specified in these terms, intellectual property of submitted works always belongs to the participants. The organizers do not acquire ownership of submitted works through this competition.

II. Scope of Authorization and Use

1. By submitting their work, participants agree to grant the organizers a worldwide, non-exclusive, royalty-free license for the following purposes directly related to this competition and associated academic activities:

• (1) Selection and Administrative Affairs: Including reviewing, archiving, internal communication, and necessary technical processing of submitted works;

• (2) Academic Exchange and Promotion: Displaying, presenting, or citing all or part of submitted works at academic conferences, seminars, forums, and other academic occasions;

• (3) Information Release and Dissemination: Publishing and displaying all or part of submitted works on academic platforms authorized by the organizers, official websites, public accounts, and other non-commercial communication channels;

• (4) Event Promotion: Using content or excerpts from submitted works within reasonable scope to introduce, review, or promote this competition and related academic activities.

2. The above authorization does not constitute an exclusive license for submitted works, nor does it affect participants’ right to use their works independently or authorize third parties to use them in any manner.

3. When using submitted works, the organizers should respect and reasonably protect participants’ right of attribution, indicating the author’s name or their designated attribution format.

III. Editing and Citation Standards

1. The organizers have the right to make necessary format adjustments, technical processing, or excerpt citations of submitted works without changing the core viewpoints and academic positions, to adapt to different academic exchange or communication scenarios.

2. Except for the circumstances described in the preceding paragraph, the organizers shall not substantially adapt or recreate submitted works, nor use work content in ways that may mislead the public.

IV. Sub-licensing and Third-Party Use

1. To achieve the academic exchange and promotion purposes described in Article II of these terms, the organizers may sub-license the use rights of submitted works to cooperating academic institutions, academic conference organizers, or non-profit academic publishing platforms.

2. The organizers shall ensure that the aforementioned third parties comply with the provisions of these terms regarding non-commercial use, protection of attribution rights, and no substantial adaptation when using submitted works.

V. Commercial Use and Award Recognition

1. The organizers commit not to using submitted works for direct commercial profit-making purposes.

2. Participants have the right to truthfully state in their academic credentials, personal introductions, and legitimate academic activities that their work participated in or won awards in the “Fangtang AI4H Global Essay Competition.”

3. Without the written consent of the organizers, participants shall not use this competition or award recognition to engage in activities that may cause the public to mistakenly believe the organizers endorse specific commercial products or services.

VI. Rights Guarantee and Liability

1. Participants warrant that their submitted work is original or that they have legally obtained necessary authorization, and that there are no circumstances of infringing upon others’ legal rights.

2. If the organizers face third-party claims due to rights defects in the submitted work itself, participants shall bear corresponding liability within the scope of their fault as stipulated by law.

3. If disputes arise from third parties’ unauthorized use or misuse of work content during the organizers’ reasonable use of submitted works, the organizers shall not bear liability arising therefrom.

VII. Other Provisions

1. Participants retain the right to publish their submitted work on other platforms, media, or publications.

2. Participants may note that the work participated in the “Fangtang AI4H Global Essay Competition” when subsequently publishing their work publicly.

3. Matters not covered in these terms shall be governed by relevant laws and regulations and prevailing academic norms.

Special Notes

Understanding “Myth”

This competition adopts an open definition of “myth.” You may understand “myth” from any of the following perspectives:

• Classical mythology (Greek, Norse, Chinese, Indian, African, and other traditions)

• Modern myth theory (Lévi-Strauss, Campbell, Barthes, Blumenberg, etc.)

• Narrative archetypes and the collective unconscious (Jung, Frye, etc.)

• “Myth” in the sense of ideological critique (Barthes, Althusser, etc.)

• Technological myths, algorithmic myths, contemporary urban legends

• Your own proposed concept of “myth”

Encouraging Cross-Cultural Perspectives

We especially welcome:

• Research on non-Western mythological traditions

• Cross-cultural mythology comparisons

• Critical reflection on “cultural biases in AI training data”

• Unique perspectives from Global South scholars

Encouraging Experimental Forms

In addition to traditional academic papers, while maintaining academic rigor and argumentative depth, we also welcome experimental narratives such as dialogue-format, correspondence, or manifesto-style writings.

Exemplary Cases (To Help Understand “AI as Academic Partner”)

1. Hypnocracy:

Andrea Colamedici is an Italian philosopher, essayist, and educator who recently gained attention for conducting a highly controversial “philosophical demonstration experiment.” The core of this experiment is a book titled Hypnocracy: Trump, Musk, and the Architecture of Reality.

Colamedici’s methodology is highly innovative—adversarial collaboration: rather than having AI write directly, he had it generate philosophical viewpoints and concepts, which he then critiqued and rebutted using tools like GPT and Claude. This process is a form of creative “confrontation” aimed at generating new intellectual sparks. He has stated that after intense intellectual exchanges, he sometimes cannot distinguish whether a brilliant insight came from himself or the AI. This prompted him to reflect on the “distributed nature of thought”—that ideas can emerge at the intersection of different intelligences, thereby challenging the traditional, isolated concept of “authorship.”

2. Knowledge Protocol Engineering: Making AI Think Like a Historian

“Knowledge Protocol Engineering” (KPE), proposed by the team of Zhang Guangwei and Deng Rui from the School of History at Shaanxi Normal University in China, provides a key paradigm breakthrough for AI for Humanities, especially historical research. It moves beyond past approaches of simply “feeding data” to AI (such as RAG—Retrieval-Augmented Generation) or giving it a set of “general tools” (through Agents), toward systematically injecting “research methodology.”

This paradigm aims to design historians’ tacit workflows (such as the thought processes of authentication, verification, and analysis) and procedural knowledge (such as analytical standards for specific types of documents) into explicit “protocols” that AI can strictly execute. This enables a general large language model to engage in structured, step-by-step logical reasoning under the constraints and guidance of protocols, thereby avoiding the instability and unreliability issues of traditional AI assistants, making behavior transparent and interpretable. The research team recognized from the practical failures of building historical source analysis agents that in professional fields, endowing AI with “discipline” and “method” is more important than merely giving AI “freedom.” KPE transforms expert “craft” into reproducible, scalable “procedures.” This not only constructs research assistants that truly understand academic standards but also profoundly advances the research process from a “craft” model dependent on individual experience toward a new research science of human-AI collaboration with programmable methods.

3. Philosopher Agents:

Multiple philosopher AI agents are configured to represent different schools of thought and engage in simulated dialogues around specific propositions. Through a design where the philosopher is “in the loop,” the system can imitate their reasoning style; while the researcher remains “over the loop,” guiding the dialogue direction and distilling new perspectives that transcend any single agent. For example, when discussing “free will,” a Confucian agent might emphasize how social ethics shapes choices, while an existentialist agent might assert the individual’s absolute autonomy. The researcher does not directly intervene in the debate but rather, by adjusting the dialogue framework or introducing new propositions, prompts the agents to generate new concepts through their exchanges—this is neither a predetermined conclusion nor a simple collage, but an inspiring intellectual landscape that emerges from dynamic interaction. This model transforms AI into a “resonance chamber” (Gilles Deleuze) for thought experiments, giving classical philosophy new life and possibilities through generative dialogue.

4. The World History Lab: Building Explanatory Models with “High-Dimensional Historical Data”
Led by Oxford scholar Pieter François, the World History Lab translates core historical questions—using AI and related tools—into a set of explanatory models that can be tested empirically. Its aim is to identify patterns in world history through quantitative methods over long timescales. The research team encodes evidence scattered across archaeological materials, chronicles, institutional histories, and records of religious rituals into traceable, auditable variable systems (which can reach thousands of dimensions). They then use statistical inference and computational modeling to evaluate the explanatory power of hypotheses about social complexity, institutional formation, war mobilization, and religious–ritual structures. Crucially, this approach does not reduce history to clean data; instead, it treats uncertainty, contestation, and gaps in the sources as part of the modeling process itself. Through explicit variable definitions, evidence-chain annotation, and reproducible coding protocols, it enables scholars to debate and verify findings within a shared analytical framework.

As an exemplary attempt for integrating AI into historical research, this case both sketches a pathway for AI-assisted cross-cultural comparative work and advances a new theoretical account of how historical data can be used to produce and test explanations.

Frequently Asked Questions (FAQ)

Q1: Must I use a specific AI system?

A: No. You may use any large language model (Claude, GPT-4, Gemini, DeepSeek, Ernie Bot, etc.), and you may even use multiple systems simultaneously for comparison.

Q2: Does AI-generated content count as plagiarism?

A: The key is how you use it. If you simply have AI write a paper and put your name on it, that is academic misconduct. But if AI is your dialogue partner, helping you deepen your thinking, that is legitimate collaboration. You must honestly explain AI’s participation in the “AI Collaboration Appendix.”

Q3: My research doesn’t involve the literal meaning of “myth.” Can I still submit?

A: Yes. “Myth” can also be broadly understood as any “narrative mechanism for generating meaning.” You may study historical narratives, literary fiction, philosophical metaphors, scientific paradigms, etc., as long as it relates to “meaning production in the age of AI.”

Q4: I’m worried AI will “mislead” my research.

A: This is precisely the critical attitude we encourage! You should reflect on AI’s limitations, biases, and errors in your paper. Demonstrating how you identified and corrected AI’s problems is itself an important scholarly contribution.

Q5: How will reviewers evaluate “AI collaboration quality”?

A: What we value is: the quality of the human-AI collaboration process and the innovation and inspiration of the methods. We will examine: AI’s unique contribution to the research process, the quality of the human’s guidance, rebuttal, and correction of AI, and based on the author’s own creative practice, the author’s reflection on “AI for Humanities” as a new paradigm.

This call has concluded. The historical text is preserved here as a record of the competition.