# Back to the Present: How Not to Use Counterfactuals to Explain Causal Asymmetry

## Abstract

**:**

## 1. Introduction

## 2. Time-Travelling Tina

_{2}) to the start of the day at the beach (time t

_{1}) by reliable nomic and causal means, as represented in Figure 1. In Figure 1, ‘Tina-at-home’, ‘Tina-arrived-at-beach’, and ‘Tina-tanned’ refer to Tina at different spatiotemporal locations (assuming no particular metaphysics of persistence). Tina-at-home and Tina-tanned occupy different spatial locations, but the same temporal location. Tina’s time travel may occur via curves in spacetime or other physical means. For simplicity, assume that Tina does not age significantly when she travels.

- If Tina-at-home were to shave, Tina-arrived-at-beach would be beardless.
- If Tina-at-home were not to shave, Tina-arrived-at-beach would be bearded.

- 3.
- If Tina-at-home were to shave, Tina-tanned would be beardless.
- 4.
- If Tina-at-home were not to shave, Tina-tanned would be bearded.

- 5.
- If Tina-at-home were to shave, Tina-arrived-at-beach would be beardless, but her beard would grow back, reattach, or otherwise return by later that day.

## 3. Upshots for Explaining Causal Asymmetry

**D1**. Apply a statistical postulate that, roughly put, takes complete microscopically specified counterfactual worlds compatible with the above partial characterisation to be each equally probable. The probability distribution over microscopically specified counterfactual worlds implies probabilities of macrostates at any given time—which are the counterfactual consequents.

**D1**then the probability of

**B**would be x’ is true just in case Pr(

**B**/

**M**(t)&

**D**(t)) = x, where

**B**is a macroscopic event,

**M**(t) is the macroscopic state of the world at t,

**D**is the decision at t (compatible with the macrostate

**M**(t)), and Pr is a chance function evaluated using statistical mechanical probabilities.6 For example, were a particular decision

**D1**to be made at t, an event

**B**would occur with high probability, just in case

**B**’s probability is high, given

**D1**(t)

**,**and given the macrostate of the actual world at the time of

**D**remains as it is in the actual world (that is, given

**M**(t)).

given the macrostateMof the world (including the agent’s brain) the various decisions that are available to her are all equally likely. Decisions are thus indeterministic relative to the macro state of the brain and environment prior to, and at the moment of, making the decision. This indeterminacy captures the idea that which decision one makes is ‘open’ prior to making the decision.

## Funding

## Informed Consent Statement

## Conflicts of Interest

## Notes

1 | The case will not rely on gender-swapping or anything like that. |

2 | Plausibly, her having no knowledge of her state at the beach is a requirement on her reasonably deliberating about her decision [19]. One might argue that causal loops involving the agent’s decisions are unavoidable in cases of backwards time travel, even if Tina travels into the far distant present. If Tina’s case involves a causal loop, it is perhaps less surprising that methods of evaluating counterfactuals fail. See [11,13,20,21,22,23] for discussion for some of the difficulties evaluating counterfactuals in cases involving causal loops. My concerns with holding the distant present fixed are unrelated to causal loops. |

3 | Ideally, one would also want some independent motivation for the requirement. The standard Lewisian motivation [24] is to recover our intuitive judgements, but that is no help when the intuitions are in question or favour an alternative. |

4 | While [3] (pp. 30–31) might be thought to attempt a non-causal solution, his solution is temporally asymmetric and has a causal flavour, particularly regarding his talk of ‘infection’. |

5 | Loewer [29] uses probabilities in place of counterfactuals, but uses the same requirements for how each are evaluated and takes counterfactual structure to derive from probabilistic structure [29] (p. 132). Albert’s original account [6] (chapter 6) is ambiguous but is often interpreted as holding the distant present fixed [30] (p. 27). Albert confirms (private communication) that this is what he had in mind. Kutach [8] (pp. 234–236) uses the requirement to explain why we cannot influence the past by means of our forwards influence. While Kutach accepts that this asymmetry of influence may not hold in time travel scenarios [8] (p. 229), he does not take the requirement itself to be problematic when explaining temporal asymmetries. |

6 | Statistical mechanical probabilities are derived from taking the Lebesgue probability measure over microstates compatible with the low-entropy macrostate of the early universe—the ‘Past Hypothesis’—and conditionalising over later macrostates [7] (p. 317). |

7 | |

8 | What if there are no macro signatures of a past (or future) event contained in the present? Loewer [7] (p. 318) responds that, in that case, the past (or future) event will not probabilistically depend on the present decision. Loewer’s explanation of the asymmetry fails, however, if the decision is the only record of the past event in the present [30]. I discuss this kind of case below. |

9 | At least on a standard Lewisian counterfactual account of causation [24]. Again, Loewer is not explicit about the precise relation between counterfactuals and causal relations. |

10 | Could Tina’s case be ruled out because it implies violations of thermodynamic asymmetries? It is controversial whether time travel (along time-like curves) implies such violations [33] (p. 137), but, to make this response sufficiently general, one would need to argue that backwards causation implies violations of thermodynamic asymmetries, and it is precisely to be shown, not assumed, that the direction of causation is to be explained in statistical mechanical or thermodynamic terms when giving statistical mechanical explanations of causal asymmetry. |

11 | Causal methods of evaluating counterfactuals face difficulties dealing with causal structures such as causal loops—see [11,13,20,21,22,23] for discussion. Note that the standard ways of dealing with counterfactuals in cases of causal loops will not help Loewer either—standard accounts presume either temporal asymmetry [11,21,22,23] or are causal [13,20]. See [18] for discussion. |

12 | A similar point holds for accounts that use probabilities rather than counterfactuals to explain causal asymmetry [29]. Causal methods of evaluating probabilities cannot be used if the project is to explain causal asymmetry using probabilities. |

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**Figure 1.**Tina’s spatial location as a function of time. The dashed line indicates a form of time travel (whether continuous or discontinuous).

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Fernandes, A.
Back to the Present: How Not to Use Counterfactuals to Explain Causal Asymmetry. *Philosophies* **2022**, *7*, 43.
https://doi.org/10.3390/philosophies7020043

**AMA Style**

Fernandes A.
Back to the Present: How Not to Use Counterfactuals to Explain Causal Asymmetry. *Philosophies*. 2022; 7(2):43.
https://doi.org/10.3390/philosophies7020043

**Chicago/Turabian Style**

Fernandes, Alison.
2022. "Back to the Present: How Not to Use Counterfactuals to Explain Causal Asymmetry" *Philosophies* 7, no. 2: 43.
https://doi.org/10.3390/philosophies7020043