Author Archives: Peter Huggins

Bryant’s Epistemology for Scientific Metaphysics

Intro

In response to Chakravartty’s defense of a scientific metaphysics, Amanda Bryant believes that there is a need for an epistemological infrastructure for this field of philosophy. She then goes through options for constructing this infrastructure. First, she gives the option of using an empiricist epistemology, saying “we should tie metaphysics to science because the road to knowledge is empirical, and because science seems to be a paragon of empirical investigation.” However, this would not be a great option, as mixing metaphysics and scientific evidence would not call for the need of scientific evidence. Also, science isn’t always purely empirical. Bryant uses the examples of evolutionary biology, string theory, and cosmology to support her point. 

Another option she goes through is one in which scientism is the only way of knowing: “if it were the case that science should guide all inquiry, then of course it should follow that it should guide metaphysics.” However, this view quickly becomes difficult to defend, as it is far too strong. Just as we would expect a philosopher to appeal to the sciences to prove their points regarding the nature of reality, we would not expect a philosopher to appeal to science when investigating subjective things, such as justice, beauty or morality. I did, however, take issue with the idea that beauty is not something that can be scientifically proven, as there are ratios and aesthetic patterns that have proven attractive to the human eye. Because of the flaws of these two prima facie options, Bryant believes that a weaker epistemic infrastructure can do the job of supporting naturalistic prescriptions and establishing scientific metaphysics as the better option. 

Scientific Metaphysics

Bryant then begins to explain what she means when she says “scientific metaphysics.” She uses its contrast, “free range metaphysics,” which is only nominally constrained by science and focuses on “simplicity, consistency, intuitive plausibility, and explanatory power” (4) to highlight the fact that scientific metaphysics is closely associated with science. Scientific metaphysics is, in every way, engaged with science. Basically, Bryant believes scientific metaphysics to allow the philosopher to behave like a scientist, incorporating scientific data into metaphysical theories, drawing philosophical conclusions on the basis of scientific data, and other things. Any metaphysics that does some of these things that Bryant prescribes is a scientific metaphysics. Bryant believes that, while there are numerous ways that people can perceive scientific metaphysics, the common ground they can all agree on is that metaphysical speculation should be reigned in (4).

Epistemic Principles

Bryant then goes into the epistemic principles of a scientific metaphysics. It is at this point where  there could be a split in how Bryant’s scientific metaphysics could be perceived. Much of science is done in an exploratory manner. In order to understand the world, scientists need to be exposed to everything that is in this world, even if they do not officially understand it. However, the principles that Bryant lays out are not conducive to discovering new things. Instead, they are focused on justifying, and certifying, the things that scientists have already been exposed to. Her goal for scientific metaphysics is a “convergence towards a theory consilient with and strongly confirmed by the best available evidence at the time” (5). This is where Bryant and Chakravartty most strongly agree. While scientists might not understand the nature of a thing, dispositions allow them to understand what a thing does, which is better than having nothing at all.

            In order to achieve this goal, Bryant believes that science needs theoretical constraints. Theories should be adequate with, and be able to explain, the data. She also acknowledges that science sometimes requires that the theories need to be in line with political or ideological goals, which does not seem very scientific, at least to me.

            Bryant posits that these constraints fall on a spectrum of strength, with data being the affecting variable. The reason being, the more data there is, the less theoretical content there will be. Having a robust theory with fewer atomic propositions (less permissive) will lead scientists to develop stronger theories. Bryant uses the metaphor of a bouncer at a club, saying that a club that lets anybody in is not a good club. Basically, she says that by limiting the scope of inquiry, science can develop stronger theories. However, she does not claim that these more constrained theories are superior. She acknowledges that extremely constrained theories “cannot say much at all” (7). Bryant just wants there to be limits for what a theory should include; while metaphysical claims should be allowed, science should lean more towards aligning with the available data.

            Bryant’s gripe with permissive theories is that they have very little explanatory power. There is too much going on. Contrast that with a robust theory: given the fewer things going on, the theory can focus on its most relevant aspects. Bryant does allow that simply being robust is not a good reason to adopt a theoretical constraint. Neither should we give up on a constraint only because it is permissive. This stipulation brings up an important ethical question: if the selection of theoretical constraints should be well-motivated, how can the scientific community ensure that the motivations they have are good ones? This issue is immediately confronted when Bryant says that a theory that allows “too many claims for the purposes of explanation” is not strong enough. That seems to be a dangerous proposition. There should be room for every kind of reaction — the good ones should get the most attention.

Constraint Principles

Bryant posits three constraint principles: weak, moderate, and strong. Explaining the three theories, Bryant says “the weak principle makes robustly constrained theories preferable ceteris paribus, the moderate principle makes them preferable full-stop; the strong principle makes robust constraint a necessary condition of what I call epistemic adequacy” (8). In order to be epistemically adequate, people should be able to rationally adopt a policy concerning the theory or its component parts. Bryant explains that this is why her scientific metaphysics would not be conducive to discovery. Regarding justification, Bryant states that robust constraints might lead to the discrediting of some theories. As the amount of available data grows, the theory might get disconfirmed. Due to this fact, Bryant worries that constraint might not be the best way to go about justifying theories. This makes no sense to me, as justifying a false theory seems to be an ethical issue in an of itself. Thankfully, Bryant does want to allow disconfirmation to be a part of the process, which takes care of that issue. 

Epistemic Principles Defended

Much like Okham’s Razor, Bryant believes that by limiting the theoretical contents in a theory, the more likely the theory is to be true.

Argument for Statistical Likeliness

P1) Ceteris paribus, relatively simple theories are statistically likelier to be true than their more complex rivals

P2) Ceteris paribus, statistically likelier theories are epistemically preferable

P3) Robustly constrained theories are relatively simple

P4) Robustly constrained theories are statistically likelier to be true than their more complex rivals

C) Ceteris paribus, robustly constrained theories are epistemically preferable

Bryant understands that there are trade-offs for her theory. While there are many desires for a theory, “it is better to have a descriptive and explanatory theory this is only somewhat likely than to have a theory that is not particularly descriptive or explanatory, but a good deal likelier” (12). Instead, the desire is to have a principle that leads us to align with the theory that is simpler, all other things being equal.

Argument from Agreement

P1) Ceteris paribus, relatively simple theories are more conducive to agreement

P2) Ceteris paribus, theories that are more conducive to agreement are epistemically preferable

P3) Robustly constrained theories are relatively simple

C) Ceteris paribus, robustly constrained theories are epistemically preferable

By following this argument, Bryant sees two valuable outcomes: greater statistical likeliness and greater consensus. Given that these values are important for epistemic aims, it follows that robustly constrained theories should be preferred, ceteris paribus.

Argument from falsehood avoidance

P1) The more content we exclude from a theory and the less we permit, the more likely we are to avoid substantial falsity

P2) Ceteris paribus, theories that are more likely to avoid substantial falsity are epistemically preferable 

P3) Robustly constrained theories exclude relatively many putative theoretical contents and permit relatively few

C) Ceteris paribus, robustly constrained theories are epistemically preferable  

By saying less, one is less likely to say something false. Theories aim to acquaint their audiences with facts, and it is more efficient to randomly state things in the hope that they will turn out to be true.

Argument from methodological expediency

P1) Theories that better target the relevant facts are epistemically preferable 

P2) Ceteris paribus, robustly constrained theories better target the relevant facts

C) Ceteris paribus, robustly constrained theories are epistemically preferable

By adopting this argument, this allows scientists to more effectively target facts. However, not looking at certain things does not in and of itself lead to more efficient targeting. Bryant uses the metaphor of shining a flashlight in a dark room to illustrate her point.

Scientific Metaphysics and Robust Constraint

By aligning itself more with science, scientific metaphysics naturally adopts more robust constraints. These constraints do not rule out crank hypotheses, but that does not mean it encourages them. Instead, they are simply not paid any attention, or at leas they should not. It also discourages science to engage with claims that cannot be empirically proven. Now that scientific metaphysics is robustly constrained, there is now an epistemic infrastructure that allows us to properly pursue it.

Dispositional Realism and Scientific Metaphysics

Intro

Chapter 4 marks a change in focus for Chakravartty’s project. In Part II, he begins looking at “more detailed illustrations of putative exercises in scientific ontology” (C, 99). However, Chakravartty stays away from explicit scientific content, instead deciding to focus on implicit scientific content, as it has been discussed far less and provides better examples of morals for scientific ontology (C, 100). In the supplementary reading, Amanda Bryant seeks an epistemological framework for a scientific metaphysics. In order to do so, she attempts to define a principle that prefers the simpler of two scientific theories. Bryant uses Okham’s razor as a mechanism to prove that a well-constrained, robust theory, is epistemologically preferable to a permissive, less-robust theory (this will be discussed in greater detail later).

Dispositions

The main thrust of Chakravartty’s argument in this chapter centers around the subject of dispositions. He starts out with an examination of dispositional properties, defining a disposition as “the ancient idea of a causal power,” and “a property that causes something to behave in a certain way” (C, 100). These properties contrast with categorical properties. A categorical property is static by nature. For example, the length of an object is always the same. Dispositional properties, however, can differ by circumstance. For example, the fragility of an object can differ depending on its surrounding environment. Bryant implicitly touches on this in her paper, as she discusses permissive and constrained theories. She posits that constrained theories are more likely to be true. Proponents of empiricism, and therefore constrained theories, are more agreeable to categorical properties, while dispositional realists (scientific metaphysicians) tend to side more with dispositional properties, which lend themselves to more permissive theories, or at least it appears that way on the surface. This will be discussed more later. 

Dispositions used to be a fixture of philosophy, but fell on hard times during the early modern era. This might have been a result of the early modern’s tendency to split away from science (thanks for the history lesson, Professor). This ideological split makes sense, as dispositions allow for explanations of phenomena that would otherwise go unexplained. Scientists may ask why a certain entity behaves in “x” way. A dispositional realist would answer that the entity in question is disposed to behave that way (C, 101). Empiricists reject this view. Instead, they would say that there is nothing to explain past those phenomena simply existing. Although Chakravartty finds dispositions compelling, he does not believe that dispositional properties prove the existence of dispositions.

Scientific Realism

Chakravartty posits that dispositions can provide common ground for opposed aspects of scientific realism: entity and structural realism. Without dispositional realism, they are incompatible viewpoints. Dispositions are agreeable with entity realism because properties can be considered dispositions. Entity realists find these to be important, as they prove the existence of certain entities (C, 107). Regarding structural realism, dispositions can also serve as relations, as dispositions dictate how the manner in which the environment is supposed to behave. Dispositional realism reconciles the two opposing viewpoints, while also unifying our concepts of entities and properties with the causal process (C, 110). Chakravartty further drives this point home, positing that scientific laws are usually just relations between properties. This fact also does work for the dispositional realist, as properties are unified with all kinds. Chakravartty finishes this section by stating that, by finding dispositional realism attractive, one must in some way agree with scientific realism. However, as he recognizes, due to the metaphysical inferences, most people who agree with this position were already in his camp, or as he said, he is “preaching to the converted.”

Explanatory Power

One might think that there is a philosophical stalemate between dispositional properties and its deflationary analyses. However, there are new, transcendental arguments for dispositions. 

            P1: Objectionable claim regarding scientific practice

            P2: The giving of relevant explanations presupposes Q (the reality of dispositional   properties)

            C: Dispositional realism

Chakravartty then moves to discussing the two main arguments that concern explanatory practice. The first argument comes in two flavors, dispositional regress and dispositional exercise. The second argument is the argument from abstraction.

Chakravartty starts with the dispositional regress and exercise arguments. For regress, Chakravartty starts by stating that dispositional concepts explain the behavior of entities. Basically, what he says is that as scientists discover more, which should dispel the need for dispositions, there will always be new, finer grained issues that cause the need for even more dispositions (C, 113). 

He then goes through the disposition exercise argument. This argument centers on the fact that sometimes dispositional properties are acting, or “triggered,” without the actual manifestation of a certain behavior. Chakravartty uses an example from Nancy Cartwright, describing two negatively charged particles that are exactly balanced. Despite the undeniable forces at play, the particles do not move. Without an appeal to dispositional realism, there is no explanation for this event. This argument makes a case for dispositional realism, as dispositions can exercise without manifesting, which is something that categorical properties cannot do. It is important to mention that these exact situations (which are inherently inexplicable without dispositions) prove that Bryant’s epistemological framework for scientific metaphysics are more apt for justification, and not discovery. 

Lastly, Chakravartty goes through the argument for abstraction. Transcendental in nature, it is focused on the efficacy of scientific methodology in case of abstraction (C, 117). Basically, he argues that abstractions could not be used, if not for the fact that they reveal information about dispositions. As an example, Chakravartty uses the application of laws from one closed system being transferred into another, non-isolated system. Closed conditions abstract from naturally occurring phenomena in this world, and laws only describe isolated systems. However, scientists regularly apply this knowledge to non-isolated systems. Chakravartty argues that laws should be interpreted as describing dispositions, saying “such dispositions often play a role in more complex situations, even if the precise manifestations they produce in isolation are mitigated or altered when combined with other dispositions” (C, 118-9). However, there are no guarantees about successfully exporting knowledge into more complex systems. Due to the lack of this guarantee, Chakravartty posits that abstraction provides no argument for the reality of dispositions (C, 120). Dispositions could just be the result of circumstance interacting with categorical properties.

Consolidating Scientific Knowledge

Chakravartty then moves towards the explanation of his argument. He allows that the conclusions of his prior efforts to explain science result in conflicting judgements, in which incompatible models incorporate incompatible assumptions. However, he believes that dispositions can rectify this problem. Chakravartty acknowledges the fact that models and theories often end up producing inconsistent descriptions (C, 121). However, being able to resolve these different descriptions into a unified picture would be good in the pursuit of knowledge. He uses water as an example. Water is a continuous, incompressible medium. It is also a collection of discrete particles. However, an entity cannot be both a continuous medium and a collection of discrete particles. 

            Incompatibility, to the dispositional realist, could just be a description of the different dispositions. Rather than attempting to describe what a fluid is, Chakravartty believes that dispositional realism could allow us to know what a fluid does. In other words, dispositions allow us to look at the behavior of an entity instead of its nature. This is where Bryant’s thesis is applicable; by constraining their hypotheses, scientists can increase the likelihood that those hypotheses are correct, which, in turn, makes them epistemologically preferable. The resulting concern is that dispositional realists have strayed from the pursuit of science — science is supposed to be about discovering and justifying the nature of entities (C, 124). Through an empiricist lens, that pursuit would be achieved by understanding the properties of an entity. However, it is important to remember that for dispositional realists, properties are dispositions. Chakravartty says it better:

“Thus, a description of the dispositions of something to behave in the ways it does, under the kinds of circumstances that elicit those manifestations, is unavoidably part of the description of the nature of the thing” (C, 124). 

            So what does dispositional realism do? According to Chakravartty, it’s a placeholder (C, 124). Saying what a thing does is much more flexible than what a thing is. So, although it is not as strong, dispositional realism does serve a purpose. Bryant agrees, saying that “it is better to have a descriptive and explanatory theory that is only somewhat likely than to have a theory that is not particularly descriptive or explanatory, but a good deal likelier” (B, 12). Until scientists can truly discover the nature of things, dispositions give them something to work with. By not making a genuine ontological commitment, the dispositional realist helps themselves. Furthermore, as Chakravartty posits, discussing the relevant dispositions of a thing is to describe the ontology of said thing (C, 126). He knows that this does not settle the perennial debate, but thinks that this is a step in the right direction. 

Property Identity

Chakravartty then confronts the issue of what makes a given property the property that it is, as opposed to another. His answer: the dispositions. Empiricists say that properties are “quiddities,” which basically posit that the nature of the property itself is unknowable (C, 129). Bryant agrees with this evaluation, which is why she sides with Chakravartty in promoting scientific metaphysics. Nothing can be said about a given property other than it is different than other properties. This is the big logical conflict with the empiricist ideology that Chakravartty wants to point out: the philosophy that holds itself as the best method of observation, but also holds that it cannot describe the differences it discovers. Chakravartty allows that science cannot answer everything. Metaphysics will still have some role to play. Bryant buttresses Chakravartty’s opinion, saying “we should tie metaphysics to science because the road to knowledge is empirical, and because science seems to be a paragon of empirical investigation” (B, 2).