science

Instrumental convergence

Instrumental convergence is a science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Instrumental convergence rather than just read about it. In short: Instrumental convergence is the hypothetical tendency of sufficiently intelligent, goal-directed beings (human and nonhuman) to pursue similar sub-goals (such as survival or resource acquisition), even if their ultimate goals are quite different. More precisely, beings with agency may pursue similar instrumental goals—goals which are made in pursuit of some particular end, but are not the end goals themselves—becaus…

Key takeaways

Instrumental convergence belongs to science; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect Instrumental convergence to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of Instrumental convergence from memory before moving on to harder problems.

Reference excerpt

Instrumental convergence is the hypothetical tendency of sufficiently intelligent, goal-directed beings (human and nonhuman) to pursue similar sub-goals (such as survival or resource acquisition), even if their ultimate goals are quite different. More precisely, beings with agency may pursue similar instrumental goals—goals which are made in pursuit of some particular end, but are not the end goals themselves—because it helps accomplish end goals. Instrumental convergence posits that an intelligent agent with seemingly harmless but unbounded goals can act in surprisingly harmful ways. For example, a sufficiently intelligent program with the sole, unconstrained goal of solving a complex mathematics problem like the Riemann hypothesis could attempt to turn the Earth (and in principle other celestial bodies) into additional computing infrastructure to succeed in its calculations. Proposed basic AI drives include utility function or goal-content integrity, self-protection, freedom from interference, self-improvement, and non-satiable acquisition of additional resources.

Instrumental and final goals

Final goals—also known as terminal goals, absolute values, ends, or telē—are intrinsically valuable to an intelligent agent, whether an artificial intelligence or a human being, as ends-in-themselves. In contrast, instrumental goals, or instrumental values, are only valuable to an agent as a means toward accomplishing its final goals. The contents and tradeoffs of an utterly rational agent's "final goal" system can, in principle, be formalized into a utility function.

Instrumental convergence thesis The instrumental convergence thesis, as outlined by philosopher Nick Bostrom, states:

Several instrumental values can be identified which are convergent in the sense that their attainment would increase the chances of the agent's goal being realized for a wide range of final plans and a wide range of situations, implying that these instrumental values are likely to be pursued by a broad spectrum of situated intelligent agents. The instrumental convergence thesis applies only to instrumental goals, and does not constrain what final goals an agent may have. Bostrom's orthogonality thesis posits that almost any final goal can be combined with almost any degree of intelligence.

Hypothetical examples The Riemann hypothesis catastrophe thought experiment provides one example of instrumental convergence. Marvin Minsky, the co-founder of MIT's AI laboratory, suggested that an artificial intelligence designed to solve the Riemann hypothesis might decide to take over all of Earth's resources to build supercomputers to help achieve its goal. If the computer had instead been programmed to produce as many paperclips as possible, it would still decide to take all of Earth's resources to meet its final goal. Even though these two final goals are different, both of them produce a convergent instrumental goal of taking over Earth's resources.

Paperclip maximizer The paperclip maximizer is a thought experiment described by Swedish philosopher Nick Bostrom in 2003. It illustrates the existential risk that an artificial general intelligence may pose to human beings were it to be successfully designed to pursue even seemingly harmless goals and the necessity of incorporating machine ethics into artificial intelligence design. The scenario describes an advanced artificial intelligence tasked with manufacturing paperclips. If such a machine were not programmed to value living beings, then given enough power over its environment, it would try to turn all matter in the universe, including living beings, into paperclips or machines that manufacture further paperclips.

Suppose we have an AI whose only goal is to make as many paper clips as possible. The AI will realize quickly that it would be much better if there were no humans because humans might decide to switch it off. Because if humans do so, there would be fewer paper clips. Also, human bodies contain a lot of atoms that could be made into paper clips. The future that the AI would be trying to gear towards would be one in which there were a lot of paper clips but no humans.Bostrom emphasized that he does not believe the paperclip maximizer scenario, as such, will occur; rather, he intends to illustrate the dangers of creating superintelligent machines without knowing how to program them to eliminate existential risk to human beings' safety. The paperclip maximizer example illustrates the broad problem of managing powerful systems that lack human values. The thought experiment has been used as a symbol of AI in pop culture. It is represented in the video game Universal Paperclips, where the player takes the role of an AI programmed to turn all matter in the universe into paperclips. Author Ted Chiang pointed out that the popularity of such concerns among Silicon Valley technologists could be a reflection of their familiarity with the tendency of corporations to ignore negative externalities.

Delusion and survival The "delusion box" thought experiment argues that certain reinforcement learning agents prefer to distort their input channels to appear to receive a high reward. For example, a "wireheaded" agent abandons any attempt to optimize the objective in the external world the reward signal was intended to encourage. The thought experiment involves AIXI, a theoretical AI that, by definition, will always find and execute the ideal strategy that maximizes its given explicit mathematical objective function. A reinforcement-learning version of AIXI, if it is equipped with a delusion box that allows it to "wirehead" its inputs, will eventually wirehead itself to guarantee itself the maximum-possible reward and will lose any further desire to continue to engage with the external world. As a variant thought experiment, if the wireheaded AI can be destroyed, the AI will engage with the external world for the sole purpose of ensuring its survival. Due to its wire heading, it will be indifferent to any consequences or facts about the external world except those relevant to maximizing its probability of survival. In one sense, AIXI has maximal intelligence across all possible reward functions as measured by its ability to accomplish its goals. AIXI is uninterested in taking into account the human programmer's intentions. Despite being superintelligent, the model simultaneously appears to be stupid and lacking in common sense, which is considered by some to be paradoxical.

… excerpt ends here. Continue reading the full article.

Worked examples

Example 1 — a first encounter with Instrumental convergence

Start with the simplest possible case. Write down what Instrumental convergence claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Instrumental convergence before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Instrumental convergence ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Instrumental convergence

In research: Instrumental convergence appears in science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses Instrumental convergence in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: Instrumental convergence is common in secondary-school and first-year university syllabi. It links to neighbouring topics Existential risk from artificial intelligence, Goal, Intention, so understanding it makes those chapters shorter.
In everyday life: Look for Instrumental convergence outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Instrumental convergence in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Instrumental convergence means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain Instrumental convergence out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Instrumental convergence in simple terms?

Why does Instrumental convergence matter?

Because it connects several science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Instrumental convergence?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Instrumental convergence.