In my exploration of the things arcane and mythical, I stumbled upon a forgotten book by Peter Norvig – Paradigms of Artificial Intelligence Programming: Case Studies in Common Lisp. My IT colleague was delighted to see it and highly recommended the study of Common Lisp as a sort of meta language. As programming languages interest me greatly and my understanding of functional programming is rather lacking (I loath Python lambdas), I decided to give it a go. What I discovered was a language with an unusual syntax (defining all structures as lists of objects), yet a potential for writing useful tools efficiently. Then, I learned various Lisp dialects were heavily used during the computer boom of 1960-80s when the US government would pump billions of dollars into military and NASA projects (machine learning, AI algorithms, behavioral simulations,, etc.). The trend died down in the early 1990s and together with it Lisps either gave rise to modern languages like Clojure (also from the Lisp family) or simply disappeared. From the old generation Scheme and Common Lisp are still in use, though less and less by the day.
Artificial Intelligence has always been an extremely vital (and interesting) field of computer science. In fact, now more than ever, as rapid growth of the Internet forces us to develop smart tools to sieve through the wild abundance of information in real-time. No wonder projects like Alexa (Amazon) or Cortana (Microsoft) are on the rise. There are 2 crucial aspects of AI that seem to garner much interest in my opinion – human language interfaces (How to make programs understand us humans in all/most of our natural languages?) and intelligent filtering algorithms (How to make programs increasingly aware of our human needs and remember them?). The second aspect involves machine learning, which delves into data extrapolation, approximation and the progressive nature of filtering algorithms. It all boils down to making computers more human and doing some (most?) of our work for us. There are many quite realistic pitfalls, of course, like algorithms deciding that humans are the limiting factor in making our (human) lives easier. When we consider emotions as a complete contradiction to reason, this makes perfect sense. Unpredictable humans are the weakest link in an approach that relies on predictable values.
Going back to Lisp and its dialects, after its inception in 1959 it quickly became the language of choice for writing mathematical algorithms, especially in the field of AI. It was clear that the Lisp S-expression syntax makes code easy to read and the language itself has a strong propensity for evolution. From more modern times (1990-2000) there are plenty of success stories on how Lisp saved the day. Finally, Lisps pioneered crucial concepts like functional recurrence, concurrency and interactive programming (the famous REPL read-eval-print-loop, nowadays a common feature of Haskell, Python and other languages). Taking all of this into consideration it is quite difficult to understand why Common Lisp (the standardized Lisp effort) stopped being the hot stuff. Some of the sources I found mentioned that Lisps were pushed aside for political reasons. Budget cuts made a lot of NASA projects struggle for survival or meet swift demise. Also, new cool languages (*cough* *cough* Perl) came to be and Lisps were supposedly too arcane to be picked up and used easily. However, to me Common Lisp seems far less verbose (obfuscated?) than for example Java and far more orderly than said Perl. Its performance is also supposedly on par with Java, which might be interesting to people who would like to write useful tools quickly (as quickly as in Python, for instance), yet not get into the memory management details of vanilla C or C++ for better performance.
The truth is that no language is really dead until it becomes naturally obsolete. Even if it suddenly loses enterprise backing. While Lisps have some viable descendants, one would be hard pressed to find a language that directly supersedes Lisps. There are of course multiple functional languages that share Lisps’ strengths, yet they typically sport a vastly less approachable syntax, devoid of easily readable S-expressions. Therefore, I believe Scheme, Common Lisp and other modern Lisps deserve not only attention, but also proper appreciation.