Ignoring Minds Leads to Bad Science

People are not just particles in motion. Intelligent entities do not cooperate with evolutionary models.

Models can be useful for crowd control, traffic optimization and other things involving human motion. But when materialists try to treat human beings like other organisms, or like mere physical entities, their assumptions are bound to oversimplify situations and even lead to absurdities. Murphy jokes that under ideal conditions of pressure, temperature and humidity, a lab animal does what it darn well pleases. How much less can human beings, with free will and intelligence, foul up experiments when treated like lab rats? Arthur Koestler called this the Ratomorphic Fallacy. It’s still committed today by materialist scientists.

The natural selection of words: Finding the features of fitness (PLoS One). Words change over time. This is true. But do they evolve by natural selection? Peter Turney and Saif Mohammad think so.

Competition among words is analogous to biological evolution by natural selection. The leading word in a synset (the word with the highest frequency) is like the leading species in a genus (the species with the largest population). The number of tokens of a word in a corpus corresponds to the number of individuals of a species in an environment.

If this were Darwinian evolution, we should expect random mutations to be selected mindlessly. Do not human beings, the only users of syntactic and semantic language, have some choice in the matter? The symbolic meaning of randomly mutating words would lead to gibberish. Despite their lengthy excursions into Jargonwocky, this has to be one of the most absurd, misleading Darwinian theories in recent memory. These two don’t even understand Darwinism, let alone make a valid comparison with language.

As we said in the introduction, the focus of this paper is selection. Future work should consider also variation and heredity, the other two components of Darwinian evolution. There is some past work on predicting variation of words….

Not content with one Ratomorphic Fallacy, they suggest some others:

This general framework may be applicable to other forms of cultural evolution. For example, the market share of a particular brand within a specific type of product is analogous to the frequency of a word within a synset. The fraction of votes for a political party in a given country is another example.

Hopefully your investment strategy and political philosophy do not rely on blind processes of mutation and selection.

Strategies for combating online hate (Nature). Tech giants are under pressure from all sides these days: from “hate groups” that use their public forum to spread lies or disinformation, and from legitimate users who accuse their algorithms of political bias. This article goes beyond the Ratomorphic Fallacy into the Atomorphic Fallacy (treating people like particles) by expecting people to act like nodes in a network, and looking for ways their behavior might be predicted in models. Naomi Derszy summarizes a study by Johnson et al in the same issue. She shows that it’s not easy to control fools, because fools are so ingenious.

Johnson et al. show that online hate groups are organized in highly resilient clusters. The users in these clusters are not geographically localized, but are globally interconnected by ‘highways’ that facilitate the spread of online hate across different countries, continents and languages. When these clusters are attacked — for example, when hate groups are removed by social-media platform administrators (Fig. 1) — the clusters rapidly rewire and repair themselves, and strong bonds are made between clusters, formed by users shared between them, analogous to covalent chemical bonds. In some cases, two or more small clusters can even merge to form a large cluster, in a process the authors liken to the fusion of two atomic nuclei. Using their mathematical model, the authors demonstrated that banning hate content on a single platform aggravates online hate ecosystems and promotes the creation of clusters that are not detectable by platform policing (which the authors call ‘dark pools’), where hate content can thrive unchecked.

Basically, if you create an algorithm to block any group of human “atomic nuclei,” they will find ways to frustrate your models. In their paper, “Hidden resilience and adaptive dynamics of the global online hate ecology,” Johnson et al. treat “hate groups” (which consist of human beings) as organisms that evolve, bond like molecules, and engage in adaptive evolutionary mechanisms. How, then, can they judge the behaviors of evolving entities “abhorrent” or “illicit” in a moral sense? No one judges chemicals, networks and lower organisms with such terms. Seeing groups of people as adapting, evolving entities, cannot begin to fathom the complexities of language, ideas and motivation. It cheapens the meaning of humanity.

More examples of this fallacy will be shared soon. Darwinians become so infatuated with natural selection, they apply it everywhere. The Stuff Happens Law is Darwin’s hammer that sees every problem as a nail.