strong ai thesis

Artificial intelligence, aka AI (strong thesis)

Artificial intelligence, aka AI (strong thesis): the two-part thesis which says (i) that rational human intelligence can be explanatorily and ontologically reduced to Turing-computable algorithms and the operations of digital computers ...

ARTIFICIAL INTELLIGENCE, aka AI (strong thesis): the two-part thesis which says (i) that rational human intelligence can be explanatorily and ontologically reduced to Turing-computable algorithms and the operations of digital computers (aka the thesis of formal mechanism, as it’s applied to rational human intelligence ), and (ii) that it’s technologically possible to build a digital computer that’s an exact counterpart of rational human intelligence, such that this machine not only exactly reproduces (aka simulates) all the actual performances of rational human intelligence, but also outperforms it (aka the counterpart thesis ).

See also the entries on “ artificial intelligence, aka AI (weak thesis) ,” “ Turing machines ,” and “ Gödel’s incompleteness theorems .”

Controversy: The strong AI thesis is not only immensely controversial, but also strongly apt to be seriously muddled, for at least three reasons.

First, the strong AI thesis is very often confused with the weak AI thesis, but (i) the weak AI thesis is itself ambiguous as between a non-trivial version and a trivial version, and (ii) even if both of the versions of the weak AI thesis were true, nevertheless strong AI could still be false.

Second, the strong AI thesis, as such, overlooks the fact that rational human intelligence is also conscious: hence if strong AI were true, then human consciousness would also have to be explanatorily and ontologically reducible to Turing-computable algorithms and the operations of digital computers, which is equivalent to the materialist/physicalist thesis of metaphysical functionalism about the mind-body problem , which in turn puts an extra-heavy burden of proof on defenders of strong AI.

Third, the very idea of “being artificial” is ambiguous as between (i) being mechanical, as opposed to being organic , and (ii) being able to be built or constructed or synthesized, as opposed to not being able to be built or constructed or synthesized , for whatever reason, but (i) and (ii) are mutually logically independent of one another: something could be mechanical but not buildable, constructible, or synthesizable (for example, digital computations involving more digits or computations than there are particles or future moments of time in the cosmos), and conversely something could be buildable, constructible, or synthesizable but not mechanical (for example, certain exactly reproducible uncomputable, non-equilibrium thermodynamic biochemical processes, including organismic processes).*

ELABORATION

Over and above the controversies, the strong AI thesis is demonstrably false, for at least five reasons; and the weak AI thesis is either false (the non-trivial version) or boringly trivially true (the trivial version).

Necessarily, intelligent rational human minds are alive , but systems that conform to the strong AI thesis are inherently mechanical and non-living , so the strong AI thesis is necessarily false.

Necessarily, intelligent rational human minds are embodied , but systems that conform to the strong AI thesis are possibly disembodied , so the strong AI thesis is necessarily false.

Necessarily, rational human knowledge requires a non-accidental connection between judgment or belief and truth, and also a non-accidental connection between true belief and justification, but systems that conform to the strong AI thesis only ever provide accidental content-connections, so the strong AI thesis is necessarily false.

Again, necessarily, rational human knowledge requires a non-accidental connection between judgment or belief and truth, and also a non-accidental connection between true belief and justification, but systems that conform to the strong AI thesis only ever provide accidental content-connections, so if the strong AI thesis were true, then our intelligent rational human minds would be nothing more than Turing machines, and therefore we couldn’t ever know the truth of the strong AI thesis, hence the strong AI thesis is self-undermining. 5. Kurt Gödel’s incompleteness theorems (Gödel, 1931/1967), which say (i) that all Principia Mathematica -style systems of mathematical logic based on the Peano axioms for arithmetic will contain undecidable/ unprovable sentences, and (ii) that no such system of mathematical logic can prove its own consistency, hence the truth of mathematical axioms has to be demonstrated outside those systems—for example, by acts of rational human mathematical intuition —guarantee that there will be uncomputable/undecidable mathematical axioms that only intelligent rational human minds can know, so systems that conform to the strong AI thesis inherently fall short of the actual performances of rational human intelligence, and therefore the strong AI thesis is false.

Moreover, if the weak AI thesis says that not all but only some actual performances of rational human intelligence are exactly reproducible (aka can be simulated) on Turing machines (i.e., the non-trivial version), then since the strong AI thesis is not only false but impossible, then the non-trivial version of the weak AI thesis is false and impossible too.

But if the weak AI thesis says merely that some behavioral or formal features of some actual performances of rational human intelligence are either operationally or isomorphically representable on Turing machines (the trivial version), then this is indeed true, but at best boringly trivially true, since the very same thesis is true of even the simplest counting or calculating procedures, using for example one’s fingers, hockey pucks, or an abacus.

If you feel so inclined, please feel free to show your support for Robert via his Patron page (https://www.patreon.com/philosophywithoutborders) or purchase his recently published book, The Fate of Analysis (2021).

The Fate of Analysis (2021)

Robert Hanna’s twelfth book, The Fate of Analysis , is a comprehensive revisionist study of Analytic philosophy from the early 1880s to the present, with special attention paid to Wittgenstein’s work and the parallels and overlaps between the Analytic and Phenomenological traditions.

By means of a synoptic overview of European and Anglo-American philosophy since the 1880s—including accessible, clear, and critical descriptions of the works and influence of, among others, Gottlob Frege, G.E. Moore, Bertrand Russell, Alexius Meinong, Franz Brentano, Edmund Husserl, The Vienna Circle, W.V.O. Quine, Saul Kripke, Wilfrid Sellars, John McDowell, and Robert Brandom, and, particularly, Ludwig Wittgenstein— The Fate of Analysis critically examines and evaluates modern philosophy over the last 140 years.

In addition to its critical analyses of the Analytic tradition and of professional academic philosophy more generally, The Fate of Analysis also presents a thought-provoking, forward-looking, and positive picture of the philosophy of the future from a radical Kantian point of view.

You might also like

Analytic-Synthetic

Free Agency

Epistemology

Analytic Philosophy

• Resources Home 🏠
• Try SciSpace Copilot
• Search research papers
• Add Copilot Extension
• Try AI Detector
• Try Paraphraser
• Try Citation Generator
• April Papers
• June Papers
• July Papers

AI for thesis writing — Unveiling 7 best AI tools

Table of Contents

Writing a thesis is akin to piecing together a complex puzzle. Each research paper, every data point, and all the hours spent reading and analyzing contribute to this monumental task.

For many students, this journey is a relentless pursuit of knowledge, often marked by sleepless nights and tight deadlines.

Here, the potential of AI for writing a thesis or research papers becomes clear: artificial intelligence can step in, not to take over but to assist and guide.

Far from being just a trendy term, AI is revolutionizing academic research, offering tools that can make the task of thesis writing more manageable, more precise, and a little less overwhelming.

In this article, we’ll discuss the impact of AI on academic writing process, and articulate the best AI tools for thesis writing to enhance your thesis writing process.

The Impact of AI on Thesis Writing

Artificial Intelligence offers a supportive hand in thesis writing, adeptly navigating vast datasets, suggesting enhancements in writing, and refining the narrative.

With the integration of AI writing assistant, instead of requiring you to manually sift through endless articles, AI tools can spotlight the most pertinent pieces in mere moments. Need clarity or the right phrasing? AI-driven writing assistants are there, offering real-time feedback, ensuring your work is both articulative  and academically sound.

AI tools for thesis writing harness Natural Language Processing (NLP) to generate content, check grammar, and assist in literature reviews. Simultaneously, Machine Learning (ML) techniques enable data analysis, provide personalized research recommendations, and aid in proper citation.

And for the detailed tasks of academic formatting and referencing? AI streamlines it all, ensuring your thesis meets the highest academic standards.

However, understanding AI's role is pivotal. It's a supportive tool, not the primary author. Your thesis remains a testament to your unique perspective and voice.

AI for writing thesis is there to amplify that voice, ensuring it's heard clearly and effectively.

How AI tools supplement your thesis writing

AI tools have emerged as invaluable allies for scholars. With just a few clicks, these advanced platforms can streamline various aspects of thesis writing, from data analysis to literature review.

Let's explore how an AI tool can supplement and transform your thesis writing style and process.

Efficient literature review : AI tools can quickly scan and summarize vast amounts of literature, making the process of literature review more efficient. Instead of spending countless hours reading through papers, researchers can get concise summaries and insights, allowing them  to focus on relevant content.

Enhanced data analysis : AI algorithms can process and analyze large datasets with ease, identifying patterns, trends, and correlations that might be difficult or time-consuming for humans to detect. This capability is especially valuable in fields with massive datasets, like genomics or social sciences.

Improved writing quality : AI-powered writing assistants can provide real-time feedback on grammar, style, and coherence. They can suggest improvements, ensuring that the final draft of a research paper or thesis is of high quality.

Plagiarism detection : AI tools can scan vast databases of academic content to ensure that a researcher's work is original and free from unintentional plagiarism .

Automated citations : Managing and formatting citations is a tedious aspect of academic writing. AI citation generators  can automatically format citations according to specific journal or conference standards, reducing the chances of errors.

Personalized research recommendations : AI tools can analyze a researcher's past work and reading habits to recommend relevant papers and articles, ensuring that they stay updated with the latest in their field.

Interactive data visualization : AI can assist in creating dynamic and interactive visualizations, making it easier for researchers to present their findings in a more engaging manner.

Top 7 AI Tools for Thesis Writing

The academic field is brimming with AI tools tailored for academic paper writing. Here's a glimpse into some of the most popular and effective ones.

Here we'll talk about some of the best ai writing tools, expanding on their major uses, benefits, and reasons to consider them.

If you've ever been bogged down by the minutiae of formatting or are unsure about specific academic standards, Typeset is a lifesaver.

Typeset specializes in formatting, ensuring academic papers align with various journal and conference standards.

It automates the intricate process of academic formatting, saving you from the manual hassle and potential errors, inflating your writing experience.

An AI-driven writing assistant, Wisio elevates the quality of your thesis content. It goes beyond grammar checks, offering style suggestions tailored to academic writing.

This ensures your thesis is both grammatically correct and maintains a scholarly tone. For moments of doubt or when maintaining a consistent style becomes challenging, Wisio acts as your personal editor, providing real-time feedback.

Known for its ability to generate and refine thesis content using AI algorithms, Texti ensures logical and coherent content flow according to the academic guidelines.

When faced with writer's block or a blank page, Texti can jumpstart your thesis writing process, aiding in drafting or refining content.

JustDone is an AI for thesis writing and content creation. It offers a straightforward three-step process for generating content, from choosing a template to customizing details and enjoying the final output.

JustDone AI can generate thesis drafts based on the input provided by you. This can be particularly useful for getting started or overcoming writer's block.

This platform can refine and enhance the editing process, ensuring it aligns with academic standards and is free from common errors. Moreover, it can process and analyze data, helping researchers identify patterns, trends, and insights that might be crucial for their thesis.

Tailored for academic writing, Writefull offers style suggestions to ensure your content maintains a scholarly tone.

This AI for thesis writing provides feedback on your language use, suggesting improvements in grammar, vocabulary, and structure . Moreover, it compares your written content against a vast database of academic texts. This helps in ensuring that your writing is in line with academic standards.

Isaac Editor

For those seeking an all-in-one solution for writing, editing, and refining, Isaac Editor offers a comprehensive platform.

Combining traditional text editor features with AI, Isaac Editor streamlines the writing process. It's an all-in-one solution for writing, editing, and refining, ensuring your content is of the highest quality.

PaperPal , an AI-powered personal writing assistant, enhances academic writing skills, particularly for PhD thesis writing and English editing.

This AI for thesis writing offers comprehensive grammar, spelling, punctuation, and readability suggestions, along with detailed English writing tips.

It offers grammar checks, providing insights on rephrasing sentences, improving article structure, and other edits to refine academic writing.

The platform also offers tools like "Paperpal for Word" and "Paperpal for Web" to provide real-time editing suggestions, and "Paperpal for Manuscript" for a thorough check of completed articles or theses.

Is it ethical to use AI for thesis writing?

The AI for writing thesis has ignited discussions on authenticity. While AI tools offer unparalleled assistance, it's vital to maintain originality and not become overly reliant. Research thrives on unique contributions, and AI should be a supportive tool, not a replacement.

The key question: Can a thesis, significantly aided by AI, still be viewed as an original piece of work?

AI tools can simplify research, offer grammar corrections, and even produce content. However, there's a fine line between using AI as a helpful tool and becoming overly dependent on it.

In essence, while AI offers numerous advantages for thesis writing, it's crucial to use it judiciously. AI should complement human effort, not replace it. The challenge is to strike the right balance, ensuring genuine research contributions while leveraging AI's capabilities.

Wrapping Up

Nowadays, it's evident that AI tools are not just fleeting trends but pivotal game-changers.

They're reshaping how we approach, structure, and refine our theses, making the process more efficient and the output more impactful. But amidst this technological revolution, it's essential to remember the heart of any thesis: the researcher's unique voice and perspective .

AI tools are here to amplify that voice, not overshadow it. They're guiding you through the vast sea of information, ensuring our research stands out and resonates.

Try these tools out and let us know what worked for you the best.

Love using SciSpace tools? Enjoy discounts! Use SR40 (40% off yearly) and SR20 (20% off monthly). Claim yours here 👉 SciSpace Premium

Frequently Asked Questions

Yes, you can use AI to assist in writing your thesis. AI tools can help streamline various aspects of the writing process, such as data analysis, literature review, grammar checks, and content refinement.

However, it's essential to use AI as a supportive tool and not a replacement for original research and critical thinking. Your thesis should reflect your unique perspective and voice.

Yes, there are AI tools designed to assist in writing research papers. These tools can generate content, suggest improvements, help with formatting, and even provide real-time feedback on grammar and coherence.

Examples include Typeset, JustDone, Writefull, and Texti. However, while they can aid the process, the primary research, analysis, and conclusions should come from the researcher.

The "best" AI for writing papers depends on your specific needs. For content generation and refinement, Texti is a strong contender.

For grammar checks and style suggestions tailored to academic writing, Writefull is highly recommended. JustDone offers a user-friendly interface for content creation. It's advisable to explore different tools and choose one that aligns with your requirements.

To use AI for writing your thesis:

1. Identify the areas where you need assistance, such as literature review, data analysis, content generation, or grammar checks.

2. Choose an AI tool tailored for academic writing, like Typeset, JustDone, Texti, or Writefull.

3. Integrate the tool into your writing process. This could mean using it as a browser extension, a standalone application, or a plugin for your word processor.

4. As you write or review content, use the AI tool for real-time feedback, suggestions, or content generation.

5. Always review and critically assess the suggestions or content provided by the AI to ensure it aligns with your research goals and maintains academic integrity.

You might also like

What is a thesis | A Complete Guide with Examples

How to Write a Better Thesis Statement Using AI (2023 Updated)

Table of contents

Meredith Sell

With the exceptions of poetry and fiction, every piece of writing needs a thesis statement. 

- Opinion pieces for the local newspaper? Yes. 

- An essay for a college class? You betcha.

- A book about China’s Ming Dynasty? Absolutely.

All of these pieces of writing need a thesis statement that sums up what they’re about and tells the reader what to expect, whether you’re making an argument, describing something in detail, or exploring ideas.

But how do you write a thesis statement? How do you even come up with one?

This step-by-step guide will show you exactly how — and help you make sure every thesis statement you write has all the parts needed to be clear, coherent, and complete.

Let’s start by making sure we understand what a thesis is (and what it’s not).

What Is a Thesis Statement?

A thesis statement is a one or two sentence long statement that concisely describes your paper’s subject, angle or position — and offers a preview of the evidence or argument your essay will present.

A thesis is not:

• An exclamation
• A simple fact

Think of your thesis as the road map for your essay. It briefly charts where you’ll start (subject), what you’ll cover (evidence/argument), and where you’ll land (position, angle). 

Writing a thesis early in your essay writing process can help you keep your writing focused, so you won’t get off-track describing something that has nothing to do with your central point. Your central point is your thesis, and the rest of your essay fleshes it out.

Get help writing your thesis statement with this FREE AI tool > Get help writing your thesis statement with this FREE AI tool >

Different Kinds of Papers Need Different Kinds of Theses

How you compose your thesis will depend on the type of essay you’re writing. For academic writing, there are three main kinds of essays:

• Persuasive, aka argumentative
• Expository, aka explanatory

A persuasive essay requires a thesis that clearly states the central stance of the paper , what the rest of the paper will argue in support of. 

Paper books are superior to ebooks when it comes to form, function, and overall reader experience.

An expository essay’s thesis sets up the paper’s focus and angle — the paper’s unique take, what in particular it will be describing and why . The why element gives the reader a reason to read; it tells the reader why the topic matters.

Understanding the functional design of physical books can help ebook designers create digital reading experiences that usher readers into literary worlds without technological difficulties.

A narrative essay is similar to that of an expository essay, but it may be less focused on tangible realities and more on intangibles of, for example, the human experience.

The books I’ve read over the years have shaped me, opening me up to worlds and ideas and ways of being that I would otherwise know nothing about.

As you prepare to craft your thesis, think through the goal of your paper. Are you making an argument? Describing the chemical properties of hydrogen? Exploring your relationship with the outdoors? What do you want the reader to take away from reading your piece?

Make note of your paper’s goal and then walk through our thesis-writing process.

Now that you practically have a PhD in theses, let’s learn how to write one:

How to Write (and Develop) a Strong Thesis

If developing a thesis is stressing you out, take heart — basically no one has a strong thesis right away. Developing a thesis is a multi-step process that takes time, thought, and perhaps most important of all: research . 

Tackle these steps one by one and you’ll soon have a thesis that’s rock-solid.

1. Identify your essay topic.

Are you writing about gardening? Sword etiquette? King Louis XIV?

With your assignment requirements in mind, pick out a topic (or two) and do some preliminary research . Read up on the basic facts of your topic. Identify a particular angle or focus that’s interesting to you. If you’re writing a persuasive essay, look for an aspect that people have contentious opinions on (and read our piece on persuasive essays to craft a compelling argument).

If your professor assigned a particular topic, you’ll still want to do some reading to make sure you know enough about the topic to pick your specific angle.

For those writing narrative essays involving personal experiences, you may need to do a combination of research and freewriting to explore the topic before honing in on what’s most compelling to you.

Once you have a clear idea of the topic and what interests you, go on to the next step.

2. Ask a research question.

You know what you’re going to write about, at least broadly. Now you just have to narrow in on an angle or focus appropriate to the length of your assignment. To do this, start by asking a question that probes deeper into your topic. 

This question may explore connections between causes and effects, the accuracy of an assumption you have, or a value judgment you’d like to investigate, among others.

For example, if you want to write about gardening for a persuasive essay and you’re interested in raised garden beds, your question could be:

What are the unique benefits of gardening in raised beds versus on the ground? Is one better than the other?

Or if you’re writing about sword etiquette for an expository essay , you could ask:

How did sword etiquette in Europe compare to samurai sword etiquette in Japan?

How does medieval sword etiquette influence modern fencing?

Kickstart your curiosity and come up with a handful of intriguing questions. Then pick the two most compelling to initially research (you’ll discard one later).

3. Answer the question tentatively.

You probably have an initial thought of what the answer to your research question is. Write that down in as specific terms as possible. This is your working thesis . 

Gardening in raised beds is preferable because you won’t accidentally awaken dormant weed seeds — and you can provide more fertile soil and protection from invasive species.

Medieval sword-fighting rituals are echoed in modern fencing etiquette.

Why is a working thesis helpful?

Both your research question and your working thesis will guide your research. It’s easy to start reading anything and everything related to your broad topic — but for a 4-, 10-, or even 20-page paper, you don’t need to know everything. You just need the relevant facts and enough context to accurately and clearly communicate to your reader.

Your working thesis will not be identical to your final thesis, because you don’t know that much just yet.

This brings us to our next step:

4. Research the question (and working thesis).

What do you need to find out in order to evaluate the strength of your thesis? What do you need to investigate to answer your research question more fully? 

Comb through authoritative, trustworthy sources to find that information. And keep detailed notes.

As you research, evaluate the strengths and weaknesses of your thesis — and see what other opposing or more nuanced theses exist. 

If you’re writing a persuasive essay, it may be helpful to organize information according to what does or does not support your thesis — or simply gather the information and see if it’s changing your mind. What new opinion do you have now that you’ve learned more about your topic and question? What discoveries have you made that discredit or support your initial thesis?

Raised garden beds prevent full maturity in certain plants — and are more prone to cold, heat, and drought.

If you’re writing an expository essay, use this research process to see if your initial idea holds up to the facts. And be on the lookout for other angles that would be more appropriate or interesting for your assignment.

Modern fencing doesn’t share many rituals with medieval swordplay.

With all this research under your belt, you can answer your research question in-depth — and you’ll have a clearer idea of whether or not your working thesis is anywhere near being accurate or arguable. What’s next?

5. Refine your thesis.

If you found that your working thesis was totally off-base, you’ll probably have to write a new one from scratch. 

For a persuasive essay , maybe you found a different opinion far more compelling than your initial take. For an expository essay , maybe your initial assumption was completely wrong — could you flip your thesis around and inform your readers of what you learned?

Use what you’ve learned to rewrite or revise your thesis to be more accurate, specific, and compelling.

Raised garden beds appeal to many gardeners for the semblance of control they offer over what will and will not grow, but they are also more prone to changes in weather and air temperature and may prevent certain plants from reaching full maturity. All of this makes raised beds the worse option for ambitious gardeners. 

While swordplay can be traced back through millennia, modern fencing has little in common with medieval combat where swordsmen fought to the death.

If you’ve been researching two separate questions and theses, now’s the time to evaluate which one is most interesting, compelling, or appropriate for your assignment. Did one thesis completely fall apart when faced with the facts? Did one fail to turn up any legitimate sources or studies? Choose the stronger question or the more interesting (revised) thesis, and discard the other.

6. Get help from AI

To make the process even easier, you can take advantage of Wordtune's generative AI capabilities to craft an effective thesis statement. You can take your current thesis statement and try the paraphrase tool to get suggestions for better ways of articulating it. WordTune will generate a set of related phrases, which you can select to help you refine your statement. You can also use Wordtune's suggestions to craft the thesis statement. Write your initial introduction sentence, then click '+' and select the explain suggestion. Browse through the suggestions until you have a statement that captures your idea perfectly.

Thesis Check: Look for These Three Elements

At this point, you should have a thesis that will set up an original, compelling essay, but before you set out to write that essay, make sure your thesis contains these three elements:

• Topic: Your thesis should clearly state the topic of your essay, whether swashbuckling pirates, raised garden beds, or methods of snow removal.
• Position or angle: Your thesis should zoom into the specific aspect of your topic that your essay will focus on, and briefly but boldly state your position or describe your angle.
• Summary of evidence and/or argument: In a concise phrase or two, your thesis should summarize the evidence and/or argument your essay will present, setting up your readers for what’s coming without giving everything away.

The challenge for you is communicating each of these elements in a sentence or two. But remember: Your thesis will come at the end of your intro, which will already have done some work to establish your topic and focus. Those aspects don’t need to be over explained in your thesis — just clearly mentioned and tied to your position and evidence.

Let’s look at our examples from earlier to see how they accomplish this:

Notice how:

• The topic is mentioned by name. 
• The position or angle is clearly stated. 
• The evidence or argument is set up, as well as the assumptions or opposing view that the essay will debunk.

Both theses prepare the reader for what’s coming in the rest of the essay: 

• An argument to show that raised beds are actually a poor option for gardeners who want to grow thriving, healthy, resilient plants.
• An exposition of modern fencing in comparison with medieval sword fighting that shows how different they are.

Examine your refined thesis. Are all three elements present? If any are missing, make any additions or clarifications needed to correct it.

It’s Essay-Writing Time!

Now that your thesis is ready to go, you have the rest of your essay to think about. With the work you’ve already done to develop your thesis, you should have an idea of what comes next — but if you need help forming your persuasive essay’s argument, we’ve got a blog for that.

Share This Article:

10 Longest Words in English Defined and Explained

Finding the OG Writing Assistant – Wordtune vs. QuillBot

What’s a Split Infinitive? Definition + When to Avoid It

Looking for fresh content, thank you your submission has been received.

Thesis Statement Generator

Ai-powered thesis statement creation tool.

• Create a compelling thesis for an academic paper: Generate a strong, argumentative thesis statement that clearly responds to your essay prompt.
• Develop a research question: Use your research question as a prompt to create a concise thesis statement that guides your research paper.
• Improve your argumentative essay: Create a strong thesis statement that clearly communicates your argument and sets the direction for your essay.
• Strengthen your dissertation: Develop a powerful, concise thesis statement that clearly defines the focus of your dissertation.

New & Trending Tools

Academic ai writer, ai essay expander.

MIT Technology Review

• Newsletters

Three ways the US could help universities compete with tech companies on AI innovation

Empowering universities to remain at the forefront of AI research will be key to realizing the field’s long-term potential.

• Ylli Bajraktari, Tom Mitchell, and Daniela Rus

The ongoing revolution in artificial intelligence has the potential to dramatically improve our lives—from the way we work to what we do to stay healthy. Yet ensuring that America and other democracies can help shape the trajectory of this technology requires going beyond the tech development taking place at private companies. 

Research at universities drove the AI advances that  laid the groundwork  for the commercial boom we are experiencing today. Importantly, academia also produced the leaders of pioneering AI companies. 

But today, large foundational models, or LFMs, like ChatGPT, Claude, and Gemini require such vast computational power and such extensive data sets that private companies have replaced academia at the frontier of AI. Empowering our universities to remain alongside them at the forefront of AI research will be key to realizing the field’s long-term potential. This will require correcting the stark asymmetry between academia and industry in access to computing resources.  

Academia's greatest strength lies in its ability to pursue long-term research projects and fundamental studies that push the boundaries of knowledge. The freedom to explore and experiment with bold, cutting-edge theories will lead to discoveries and innovations that serve as the foundation for future innovation. While tools enabled by LFMs are in everybody’s pocket, there are many questions that need to be answered about them, since they remain a “black box” in many ways. For example, we know AI models have a propensity to hallucinate, but we still don’t fully understand why. 

Because they are insulated from market forces, universities can chart a future where AI truly benefits the many. Expanding academia’s access to resources would foster more inclusive approaches to AI research and its applications. 

The pilot of the National Artificial Intelligence Research Resource (NAIRR), mandated in President Biden’s October 2023 executive order on AI, is a step in the right direction. Through partnerships with the private sector, the NAIRR will create a shared research infrastructure for AI. If it realizes its full potential, it will be an essential hub that helps academic researchers access GPU computational power more effectively. Yet even if the NAIRR is fully funded, its resources are likely to be spread thin. 

This problem could be mitigated if the NAIRR focused on a select number of discrete projects, as  some have suggested . But we should also pursue additional creative solutions to get meaningful numbers of GPUs into the hands of academics. Here are a few ideas:

First, we should use large-scale GPU clusters to improve and leverage the supercomputer infrastructure the US government already funds. Academic researchers should be enabled to partner with the US National Labs on grand challenges in AI research. 

Second, the US government should explore ways to reduce the costs of high-end GPUs for academic institutions—for example, by offering financial assistance such as grants or R&D tax credits. Initiatives like  New York’s , which make universities key partners with the state in AI development, are already playing an important role at a state level. This model should be emulated across the country. 

Lastly, recent export control restrictions could over time leave some US chipmakers with surplus inventory of leading-edge AI chips. In that case, the government could purchase this surplus and distribute it to universities and academic institutions nationwide.

Imagine the surge of academic AI research and innovation these actions would ignite. Ambitious researchers at universities have a wealth of diverse ideas that are too often stopped short for lack of resources. But supplying universities with adequate computing power will enable their work to complement the research carried out by private industry. Thus equipped, academia can serve as an indispensable hub for technological progress, driving interdisciplinary collaboration, pursuing long-term research, nurturing talent that produces the next generation of AI pioneers, and promoting ethical innovation. 

Historically, similar investments have yielded critical dividends in innovation. The United States of the postwar era cultivated a symbiotic relationship among government, academia, and industry that  carried us to the moon ,  seeded Silicon Valley , and  created the internet . 

We need to ensure that academia remains a strong pole in our innovation ecosystem. Investing in its compute capacity is a necessary first step. 

Ylli Bajraktari  is CEO of the Special Competitive Studies Project (SCSP), a nonprofit initiative that seeks to strengthen the United States’ long-term competitiveness. 

Tom Mitchell  is the Founders University Professor at Carnegie Mellon University. 

Is there anything more fascinating than a hidden world?

Some hidden worlds--whether in space, deep in the ocean, or in the form of waves or microbes--remain stubbornly unseen. Here's how technology is being used to reveal them.

• Mat Honan archive page

A brief, weird history of brainwashing

L. Ron Hubbard, Operation Midnight Climax, and stochastic terrorism—the race for mind control changed America forever.

• Annalee Newitz archive page

What Luddites can teach us about resisting an automated future

Opposing technology isn’t antithetical to progress.

• Tom Humberstone archive page

Africa’s push to regulate AI starts now        

AI is expanding across the continent and new policies are taking shape. But poor digital infrastructure and regulatory bottlenecks could slow adoption.

• Abdullahi Tsanni archive page

Stay connected

Get the latest updates from mit technology review.

Discover special offers, top stories, upcoming events, and more.

Thank you for submitting your email!

It looks like something went wrong.

We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at [email protected] with a list of newsletters you’d like to receive.

Die starke KI-These

The strong AI-thesis

Zu Searle's Wiederbelebung einer fragwürdigen Debatte über die Grundlagen des Erkenntnisprogramms der Erforschung Künstlicher Intelligenz (KI)

• Published: September 1991
• Volume 22 , pages 337–348, ( 1991 )

Cite this article

• Stephan Zelewski 1  

341 Accesses

Explore all metrics

The controversy about the strong AI-thesis was recently revived by two interrelated contributions stemming from J. R. Searle on the one hand and from P. M. and P. S. Churchland on the other hand. It is shown that the strong AI-thesis cannot be defended in the formulation used by the three authors. It violates some well accepted criterions of scientific argumentation, especially the rejection of essentialistic definitions. Moreover, Searle's ‘proof’ is not conclusive. Though it may be reconstructed in a conclusive manner, the modified proof is trivial. Beyond that, the most interesting aspect is formulated as an axiom that is not justified either. Therefore Searle's criticism of strong AI-thesis fails to be a convincing proof — it can be reduced to an unjustified presupposition.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price includes VAT (Russian Federation)

Instant access to the full article PDF.

Rent this article via DeepDyve

Institutional subscriptions

Similar content being viewed by others

Eino Kaila and The Vienna Circle

Mario Bunge: An Introduction to His Life, Work and Achievements

Theodore Metochites

Author information, authors and affiliations.

Seminar für Allgemeine Betriebswirtschaftslehre, Industriebetriebslehre und Produktionswirtschaft, Universität zu Köln, Albertus Magnus-Platz, 5000, Köln 41

Stephan Zelewski

You can also search for this author in PubMed   Google Scholar

Rights and permissions

Reprints and permissions

About this article

Zelewski, S. Die starke KI-These. Zeitschrift für Allgemeine Wissenschaftstheorie 22 , 337–348 (1991). https://doi.org/10.1007/BF01801214

Download citation

Issue Date : September 1991

DOI : https://doi.org/10.1007/BF01801214

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• conceptual realism
• research program
• artificial intelligence
• predicate logic
• strong AI-thesis
• Turing test
• Find a journal
• Publish with us
• Track your research

AI’s ability to write for us—and our inability to resist ‘The Button’—will spark a crisis of meaning in creative work

Soon, every major office application and email client will include a button to help you create a draft of your work. It deserves capital letters: The Button.

When faced with the tyranny of the blank page, people are going to push The Button. It is so much easier to start with something than nothing. Students are going to use it to start essays. Managers will use it to start emails, reports, or documents. Teachers will use it when providing feedback. Scientists will use it to write grants. Concept artists will use it for their first draft. Everyone is going to use The Button.

The implications of having AI write our first drafts (even if we do the work ourselves, which is not a given) are huge. One consequence is that we could lose our creativity and originality. When we use AI to generate our first drafts, we tend to anchor on the first idea that the machine produces, which influences our future work. Even if we rewrite the drafts completely, they will still be tainted by the AI’s influence. We will not be able to explore different perspectives and alternatives, which could lead to better solutions and insights.

Another consequence is that we could reduce the quality and depth of our thinking and reasoning. When we use AI to generate our first drafts, we don’t have to think as hard or as deeply about what we write. We rely on the machine to do the hard work of analysis and synthesis, and we don’t engage in critical and reflective thinking ourselves. We also miss the opportunity to learn from our mistakes and feedback and the chance to develop our own style.

AI can do it

There is already evidence that this is going to be a problem. A recent MIT study found that ChatGPT mostly serves as a substitute for human effort, not a complement to our skills. In fact, the vast majority of participants didn’t even bother editing the AI’s output. This is a problem I see repeatedly when people first use AI: they just paste in the exact question they are asked and let the AI answer it.

A lot of work is time-consuming by design. In a world in which the AI gives an instant, pretty good, near universally accessible shortcut, we’ll soon face a crisis of meaning in creative work of all kinds. This is, in part, because we expect creative work to take careful thought and revision, but also that time often operates as a stand-in for work. Take, for example, the letter of recommendation. Professors are asked to write letters for students all the time, and a good letter takes a long time to write. You have to understand the student and the reason for the letter, decide how to phrase the letter to align with the job requirements and the student’s strengths, and more. The fact that it is time-consuming is somewhat the point. That a professor takes the time to write a good letter is a sign that they support the student’s application. We are setting our time on fire to signal to others that this letter is worth reading.

Or we can push The Button.

And the problem is that the letter the AI generates is going to be good. Not just grammatically correct, but persuasive and insightful to a human reader. It is going to be better than most letters of recommendation that I receive. This means that not only is the quality of the letter no longer a signal of the professor’s interest, but also that you may actually be hurting people by not writing a letter of recommendation by AI, especially if you are not a particularly strong writer. So people now have to consider that the goal of the letter (getting a student a job) is in contrast with the morally correct method of accomplishing the goal (the professor spending a lot of time writing the letter). I am still doing all my letters the old-fashioned way, but I wonder whether that will ultimately do my students a disservice.

Now consider all the other tasks whose final written output is important because it is a signal of the time spent on the task and of the thoughtfulness that went into it—performance reviews, strategic memos, college essays, grant applications, speeches, comments on papers. And so much more.

Reconstructing meaning

Then The Button starts to tempt everyone. Work that was boring to do but meaningful when completed by humans (like performance reviews) becomes easy to outsource—and the apparent quality actually increases. We start to create documents mostly with AI that get sent to AI-powered inboxes, where the recipients respond primarily with AI. Even worse, we still create the reports by hand but realize that no human is actually reading them. This kind of meaningless task, what organizational theorists have called mere ceremony, has always been with us. But AI will make a lot of previously useful tasks meaningless. It will also remove the facade that previously disguised meaningless tasks. We may not have always known if our work mattered in the bigger picture, but in most organizations, the people in your part of the organizational structure felt it did. With AI-generated work sent to other AIs to assess, that sense of meaning disappears.

We are going to need to reconstruct meaning, in art and in the rituals of creative work. This is not an easy process, but we have done it before, many times. Where musicians once made money from records, they now depend on being excellent live performers. When photography made realistic oil paintings obsolete, artists started pushing the bounds of photography as art. When the spreadsheet made adding data by hand unneeded, clerks shifted their responsibilities to bigger-picture issues. This change in meaning is going to have a large effect on work.

Excerpted with permission from Co-Intelligence: Living and Working with AI , by Ethan Mollick, in agreement with Portfolio, an imprint of Penguin Publishing Group, a division of Penguin Random House LLC. Copyright © Ethan Mollick, 2024.

Ethan Mollick is a professor of management at Wharton, specializing in entrepreneurship and innovation. He writes the AI-focused blog One Useful Thing and is the creator of numerous educational games on a variety of topics. 

Latest in Tech

• 0 minutes ago

Finland—the world’s No. 1 coffee consumer—is turning to AI and lab-grown beans to energize the industry

Meta’s Mark Zuckerberg avoided a cage match with Elon Musk but got a jab in anyway by passing him on the billionaires list

OpenAI’s Sam Altman is funding a green-energy moonshot as AI’s power demands grow to ‘insatiable’ levels

Tesla will try to stem the bleeding on its earnings call after its worst sales quarter in four years, a round of price cuts, and a sinking share price

How to fix Boeing, according to a former Airbus technology chief

Tesla guts newly formed marketing team despite investors demanding greater focus on ads as EV sales slow

Most popular.

The outlook for home prices has changed drastically in just the past month as Fed rate cuts look more and more distant

Your reusable water bottle may be a breeding ground for strep and fecal bacteria. Here’s how to keep it clean

3 big changes coming to Medicare in 2025—and what they’ll mean for you

Former HGTV star slapped with $10 million fine and jail time for real estate fraud

Construction starts on America’s first true high-speed passenger train, between Los Angeles and Las Vegas

Exclusive: Mercedes becomes the first automaker to sell autonomous cars in the U.S. that don’t come with a requirement that drivers watch the road