@@ -60,7 +60,7 @@ By the mid 1970s, it had become apparent that the complexity of making 'intellig
- Turing tests came into question by means, among other ideas, of the 'chinese room theory' which posited that, "programming a digital computer may make it appear to understand language but could not produce real understanding."[source](https://plato.stanford.edu/entries/chinese-room/)
- The ethics of introducing artificial intelligences such as the "therapist" ELIZA into society was challenged
At the same time, various AI schools of thought began to form. A dichotomy was established between ["scruffy" vs. "neat AI"](https://en.wikipedia.org/wiki/Neats_and_scruffies) practices. 'Scruffy' labs tweaked programs for hours until they had the desired results. 'Neat' labs "focused on logic and formal problem solving". ELIZA and SHRDLU were well-known 'scruffy' systems. In the 1980s, as demand emerged to make ML systems reproducible, the 'neat' approach gradually took the forefront as its result are more explainable.
At the same time, various AI schools of thought began to form. A dichotomy was established between ["scruffy" vs. "neat AI"](https://wikipedia.org/wiki/Neats_and_scruffies) practices. 'Scruffy' labs tweaked programs for hours until they had the desired results. 'Neat' labs "focused on logic and formal problem solving". ELIZA and SHRDLU were well-known 'scruffy' systems. In the 1980s, as demand emerged to make ML systems reproducible, the 'neat' approach gradually took the forefront as its result are more explainable.
## 1980s Expert systems
As the field grew, its benefit to business became clearer, and the 1980s the proliferation of 'expert systems'. "Expert systems were among the first truly successful forms of artificial intelligence (AI) software."[source](https://wikipedia.org/wiki/Expert_system)
