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Where Is My Robot Scientist?

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Shot from the Movie AI

Mass production is something that most of us take for granted today. We enjoy the effect of it everyday but rarely think about the dramatic change it has brought to the world. Almost everything we buy today is mass produced.

One thing that’s never been able to be mass-produced is ideas. An idea can be a song, a piece of writing, a software program, or a business plan. The process of idea creation is a personal experience that requires creativity and complex thinking. It seems impossible for machines and science to create ideas like we can.

But times have changed since the day of mechanical, dumb machines that can only handle simple tasks. Recent advancements in AI and data science are giving us signs of truly “intelligent” machines, capable of mass-producing original ideas. How exactly can we do it? To answer this question, we have to understand:

  • Fundamental pieces of a mass-production system
  • Categories of ideas in the world.

Mass Production System

It’s fairly straight-forward to understand a mass-production system. People have been studying and improving it for centuries, ever since the industrial revolution (one can argue it started a lot earlier than that, but you get the point). Such systems usually involve

  • Supply chain to gather raw materials
  • Transformation process to change raw materials into generally useful, multi-purpose forms
  • Assembly lines that assemble small pieces into functional units, again, usually multi-purpose
  • Assembly lines that assemble functional units into final products
  • Quality assurance in each step

There are also distribution and fulfillment systems, but let’s focus on the creation process for now.

Categories of Ideas

Categorizing all ideas in the world is much harder. One can turn to cosmology or epistemology, but that tends to get philosophical pretty quickly. It gets even more confusing when the categories of ideas itself is an idea (hmm… did somebody say M.C Escher?) But for arguments sake, let’s group ideas into:

  • Metaphysical ideas (music, modern art - ideas for ideas sake)
  • Worldly ideas (journalism, a business plan, a piece of computer program - ideas rooted in the physical world)

Mass Producing Ideas

To imagine a mass production system for metaphysical ideas, let’s think about music. Notes/sound are the raw materials. Rhythm, riffs, choruses, movements are the small, functional units. Songs are the final products. The brute-force approach would be generating an infinite number of rhythms, riffs, choruses, create all permutation of these elements and listen to every generated song to find the ones you like. But that would take an infinite amount of time.

The key here is quality control. At each step, we identify the “quality” we care about, and create a filter to only let through what we care about. Machine learning technology can already learn “styles” of music. Rules can be created to structure pieces of music into songs, and music analytics engines + recommendation algorithms can analyze them to determine if you will like the music.

Worldly ideas on the other hand, are harder to create. There are many constraints that are hard to capture using mathematics / rules. How can we generate a piece of original news article? What about a business plan to solve a real-world problem? It seems that we have to teach machines to “understand” the real world before we can generate “analysis” from it.

But short of creating original worldly ideas, we can create derivatives of existing ideas. With sufficient data, machines can “learn” from existing ideas and create similar ideas or other forms of the same ideas. The process varies depending on the algorithm, but usually statistical analysis and natural language processing is involved. For example, text analysis engines like the SRI Internaional are able to take existing text and create short summaries from them. Diagnostic engines are able to use patient data and symptoms to create diagnosis.


The goal of mass production is a very simple economic principle: dramatic reduction on cost and dramatic increase on supply. We are still far away from creating music as good as Bach, or generating news reports worthy of the New York Times, but technologies that create ideas have fundamental impacts on society.

With SRI’s text summary technology, it now takes 10% of the time it did before to achieve the same breath in the past, which means it increased our reading speed by 1000%. Electronic music lowers the bar for music production by eliminating the necessity of learning to play musical instruments (biggest hurdle of music creation). The amount of new electronic music changed the fundamentals of the publishing side of the music industry. Companies like Game Salad try to lower the threshold for creating games, and the effect has been the commoditization of game creation. With the same level resources, my friends are way more likely to create games I want to play than Zanga ever will.

Technology is at a point to challenge the traditional method of idea creation. With the right application, we will be able to create more new ideas than ever before. And maybe one day, we will have a robot scientist making things for us.