The Washout Argument Against Longtermism

Longtermism is the view that what we choose to do now should be substantially influenced by its expected consequences for the trillions of people who might possibly exist in the longterm future. Maybe there's only a small chance that trillions of people will exist in the future, and only a minuscule chance that their lives will go appreciably better or worse as a result of what you or I do now. But however small that chance is, if we multiply it by a large enough number of possible future people -- trillions? trillions of trillions? -- the effects are worth taking very seriously.

Longtermism is a hot topic in the effective altruism movement, and William MacAskill's What We Owe the Future, released last week, has made a splash in the popular media, including The New Yorker, NPR, The Atlantic, and Boston Review. I finished the book Sunday. Earlier this year, I argued against longtermism on several grounds. Today, I'll expand on one of those arguments, which (partly following Greaves and MacAskill 2021) I'll call the Washout Argument.

The Washout Argument comes in two versions, infinite and finite.

The Washout Argument: Infinite Version

Note: If you find this a bit silly, that's part of the point.

As I've argued in other posts -- as well as in a forthcoming book chapter with philosopher of physics Jacob Barandes -- everything you do causes almost everything. Put more carefully, if we accept currently standard, vanilla physics and cosmology, and extrapolate it forward, then almost every action you take will cause almost every type of non-unique future event of finite probability. A ripple of causation extends outward from you, simply by virtue of the particles that reflect off you as you move, which then influence other particles, which influence still more particles, and so on and so on until the heat death of the universe.

But the heat death of the universe is only the beginning! Standard cosmological models don't generally envision a limit to future time.  So post heat death, we should expect the universe to just keep enduring and enduring. In this state, there will be occasional events in which particles enter unlikely configurations, by chance. For example, from time to time six particles will by chance converge on the same spot, or six hundred will, or -- very, very rarely (but we have infinitude to play with) six hundred trillion. Under various plausible assumptions, any finitely probable configuration of a finite number of particles should occur eventually, and indeed infinitely often.

This relates to the famous Boltzmann brain problem, because some of those chance configurations will be molecule-for-molecule identical with human brains.  These unfortunate brains might be having quite ordinary thoughts, with no conception that they are mere chance configurations amid post-heat-death chaos.

Now remember, the causal ripples from the particles you perturbed yesterday by raising your right hand are still echoing through this post-heat-death universe.

Suppose that, by freak chance, a human brain in a state of great suffering appears at spatiotemporal location X that has been influenced by a ripple of causation arising from your having raised your hand. That brain wouldn't have appeared in that location had you not raised your hand. Chancy events are sensitive in that way. Thus, one extremely longterm consequence of your action was that Boltzmann brain's suffering. Of course, there are also things of great value that arise which wouldn't have arisen if you hadn't raised your hand -- indeed, whole amazing worlds that wouldn't otherwise have come into being. What awesome power you have!

[For a more careful treatment see Schwitzgebel and Barandes forthcoming.]

Consequently, from a longterm perspective, everything you do has a longterm expected value of positive infinity minus negative infinity -- a value that is normally undefined. Even if you employed some fancy mathematics to subtract these infinitudes from each other, finding that, say, the good would overall outweigh the bad, there would still be a washout, since almost certainly nothing you do now would have a bearing on the balance of those two infinitudes. (Note, by the way, that my argument here is not simply that adding a finite value to an infinite value is of no consequence, though that is arguably also true.)  Whatever the expected effects of your actions are in the short term, they will eventually be washed out by infinitely many good and bad consequences in the long term.

Should you then go murder people for fun, since ultimately it makes no difference to the longterm expected balance of good to bad in the world? Of course not. I consider this argument a reductio ad absurdum of the idea that we should evaluate actions by their longterm consequences, regardless of when those consequences occur, with no temporal discounting. We should care more about the now than about the far distant future, contra at least the simplest formulations of longtermism.

You might object: Maybe my physics is wrong. Sure, maybe it is! But as long as you allow that there's even a tiny chance that this cosmological story is correct, you end up with infinite positive and negative expected values.  Even if it's 99.9% likely that your actions only have finite effects, to get an expected value in the standard way, you'll need to add in a term accounting for 0.1% chance of infinite effects, which will render the final value infinite or undefined.

The Washout Argument: Two Finite Versions

Okay, what if we forget about infinitude and just truncate our calculations at heat death? There will be only finitely many people affected by your actions (bracketing some worries about multiverse theory), so we'll avoid the problems above.

Here the issue is knowing what will have a positive versus negative longterm effect. I recommend radical skepticism.  Call this Skeptical Washout.

Longtermists generally think that the extinction of our species would be bad for the longterm future. There are trillions of people who might have led happy lives who won't do so if we wipe ourselves out in the next few centuries!

But is this so clear?

Here's one argument against it: We humans love our technology. It's our technology that creates the big existential risks of human extinction. Maybe the best thing for the longterm future is for us to extinguish ourselves as expeditiously as possible, so as to clear the world for another species to replace us -- one that, maybe, loves athletics and the arts but not technology quite so much. Some clever descendants of dolphins, for example? Such a species might have a much better chance than we do of actually surviving a billion years. The sooner we die off, maybe, the better, before we wipe out too many more of the lovely multicellular species on our planet that have the potential to eventually replace and improve on us.

Here's another argument: Longtermists like MacAskill and Toby Ord typically think that these next few centuries are an unusually crucial time for our species -- a period of unusual existential risk, after which, if we safely get through, the odds of extinction fall precipitously. (This assumption is necessary for their longtermist views to work, since if every century carries an independent risk of extinction of, say, 10%, the chance is vanishingly small that our species will survive for millions of years.) What's the best way to tide us through these next few especially dangerous centuries? Well, one possibility is a catastrophic nuclear war that kills 99% of the population. The remaining 1% might learn the lesson of existential risk so well that they will be far more careful with future technology than we are now. If we avoid nuclear war now, we might soon develop even more dangerous technologies that would increase the risk of total extinction, such as engineered pandemics, rogue superintelligent AI, out-of-control nanotech replicators, or even more destructive warheads. So perhaps it's best from the longterm perspective to let us nearly destroy ourselves as soon as possible, setting our technology back and teaching us a hard lesson, rather than blithely letting technology advance far enough that a catastrophe is more likely to be 100% fatal.

Look, I'm not saying these arguments are correct. But in my judgment they're not especially less plausible than the other sorts of futurist forecasting that longtermists engage in, such as the assumption that we will somehow see ourselves safely past catastrophic risk if we survive the next few centuries.

The lesson I draw is not that we should try to destroy or nearly destroy ourselves as soon as possible! Rather, my thought is this: We really have no idea what the best course is for the very long term future, millions of years from now. It might be things that we find intuitively good, like world peace and pandemic preparedness, or it might be intuitively horrible things, like human extinction or nuclear war.

If we could be justified in thinking that it's 60% likely that peace in 2023 is better than nuclear war in 2023 in terms of its impact on the state of the world over the entire course of the history of the planet, then the longtermist logic could still work (bracketing the infinite version of the Washout Argument). But I don't think we can be justified even in that relatively modest commitment. Regarding what actions now will have a positive expected impact on the billion-year future, I think we have to respond with a shoulder shrug. We cannot use billion-year expectations to guide our decisions.

Even if you don't want to quite shrug your shoulders, there's another way the finite Washout Argument can work.  Call this Negligible Probability Washout.

Let's say you're considering some particular action. You think that action has a small chance of creating an average benefit of -- to put a toy number on it -- one unit to each future person who exists. Posit that there are a trillion future people. Now consider, how small is that small chance? If it's less than one in a trillion, then on a standard consequentialist calculus, it would be better to create a sure one unit benefit for one person who exists now.

What are reasonable odds to put on the chance that some action you do will materially benefit a trillion people in the future? To put this in perspective, consider the odds that your one vote will decide the outcome of your country's election. There are various ways to calculate this, but the answer should probably be tiny, one in a hundred thousand at most (if you're in a swing state in a close U.S. election), maybe one in a million, one in ten million or more. That's a very near event, whose structure we understand. It's reasonable to vote on those grounds, by the utilitarian calculus. If I think that my vote has a one in ten million chance of making my country ten billion dollars better off, then -- if I'm right -- my vote is a public good worth an expected $1000 (ten billion times one in ten million).

My vote is a small splash in a very large pond, though a splash worth making.  But the billion-year future of Earth is a much, much larger pond.  It seems reasonable to conjecture that the odds that some action you do now will materially improve the lives of trillions of people in the future should be many orders of magnitude lower than one in a million -- low enough to be negligible, even if (contra the first part of this argument) you can accurately predict the direction. 

On the Other Hand, the Next Few Centuries

... are (moderately) predictable! Nuclear war would be terrible for us and our immediate descendants. We should care about protecting ourselves from pandemics, and dangerous AI systems, and environmental catastrophes, and all those other things that the longtermists care about. I don't in fact disagree with most of the longtermists' priorities and practical plans. But the justification should be the long term future in the more ordinary sense of "long term" -- fifteen years, fifty years, two hundred years, not ten million years. Concern about the next few generations is reason enough to be cautious with the world.

[Thanks to David Udell for discussion.]

The Philosophy Major Continues to Recover and Diversify in the U.S.

The National Center for Education Statistics has released their data on bachelor's degree completions in the U.S. through the 2019-2020 academic year, and it's mostly good news for the philosophy major.

Back in 2017, I noticed that the number of students completing philosophy degrees in the U.S. had plummeted sharply between 2010 and 2016, from 9297 in 2009-2010 to 7507 in 2015-2016, a decline of 19% in just six years. The other large humanities majors (history, English, and foreign languages and literatures) saw similar declines in the period.

A couple of years ago, the trend had started to modestly reverse itself -- and furthermore the philosophy major appeared to be attracting a higher percentage of women and non-White students than previously. The newest data show those trends continuing.

Methodology: The numbers below are all from the NCES IPEDS database, U.S. only, using CIP classification 38.01 for philosophy majors, including both first and second majors, using the NCES gender and race/ethnicity categories. Each year ends at spring term (thus "2010" refers to the 2009-2010 academic year).

Trend since 2010, total number of philosophy bachelor's degrees awarded in the U.S.:

2010: 9274
2011: 9298
2012: 9369
2013: 9427
2014: 8823
2015: 8186
2016: 7491
2017: 7575
2018: 7669
2019: 8075
2020: 8195

As you can see, numbers are up about 9% since their nadir in 2016, though still well below their peak in 2011. (The numbers are slightly different from those in my earlier post, presumably to small post-hoc adjustments in the IPEDS dataset.)

One consequence of the decline, I suspect, was on the job market for philosophy professors, which has been weak since the early 2010s. This has been hard especially on newly graduated PhD students in the field. With the major declining so sharply in the period, it's understandable that administrators wouldn't prioritize the hiring of new philosophy professors. If numbers continue to rise, the job market might correspondingly recover.

Total degrees awarded across all majors has also continued to rise, and thus in percentage terms, philosophy remains well below its peak of almost 0.5% in the late 2000s and early 2010s -- only 0.31% of students, a tiny percentage. Philosophy won't be overtaking psychology or biology in popularity any time soon. Philosophy majors, you are special!

Back in 2017, I also noticed that, going back to the 1980s, the percentage of philosophy majors who were women had remained entirely within the narrow band of 30-34%, despite an increase in women in the undergraduate population overall. However, in the most recent four years, this percentage rose to 39.4%. [ETA 1:48 p.m.: Since 2001, the overall percentage of women among bachelor's recipients across all majors has stayed fairly constant at around 57%.] That might not seem like a big change, but given the consistency of the earlier numbers, it's actually quite remarkable to me. Here's a zoomed-in graph to give you a sense of it:

[click to enlarge and clarify]

The philosophy major is also increasingly racially or ethnically diverse. The percentage of non-Hispanic White students has been falling steadily since NCES began collecting data in 1995, from 81% then to 58% now. Overall, across all majors, 61% percent of bachelor's degree recipients are non-Hispanic White, so the philosophy major is actually now slightly less non-Hispanic White than average. (All the race/ethnicity figures below exclude "nonresident aliens" and "race/ethnicity unknown".)

The particular patterns differ by race/ethnic group.

Native Hawaiian or Other Pacific Islanders constitute a tiny percentage: about 0.2% of degree recipients both in philosophy and overall since the category was introduced in 2011.

American Indian or Alaskan Native is also a tiny percentage, but unfortunately that percentage has been steadily declining since the mid-2000s, and the group is especially underrepresented in philosophy. According to the U.S. Census, about 0.9% of the U.S. population in that age group identifies as non-Hispanic American Indian or Alaskan Native.

[click to enlarge and clarify]

The following chart displays trends for the other four racial categories used by the NCES. In 2011, "two or more races" was introduced as a category. Also before 2011, the Asian category included "Pacific Islander".

As you can see from the chart, the percentage of Hispanic students graduating with philosophy degrees has surged, from 4.3% in 1995 to 14.4% in 2020. This is approximately representative of a similar surge among Hispanic students across all majors, from 4.8% in 1995 to 15.7% in 2020. Multiracial students have also surged, though it's unclear how much of that surge has to do with changing methodology versus the composition of the student population.

The percentage of philosophy majors identifying as Asian or Black has also increased during the period, but only slowly: From 5.4% and 3.3% respectively in 1995 to 6.8% and 5.6% in 2020. For comparison, across all majors, the numbers rose from 5.4% to 8.1% Asian and 7.6% to 10.2% Black. So, in 2020, Asian and especially Black students are disproportionately underrepresented in the philosophy major. Interestingly, some data from the Higher Education Research Institute suggests that there has been a very recent surge of interest in the philosophy major among Black students just entering college. We'll see if that plays out among Bachelor's degree recipients in a few years.

Top Science Fiction and Fantasy Magazines 2022

Since 2014, I've compiled an annual ranking of science fiction and fantasy magazines, based on prominent awards nominations and "best of" placements over the previous ten years. Below is my list for 2022. (For all previous lists, see here.)

[A DALL-E output for "science fiction and fantasy magazine"]

Method and Caveats:

(1.) Only magazines are included (online or in print), not anthologies, standalones, or series.

(2.) I gave each magazine one point for each story nominated for a Hugo, Nebula, Sturgeon, or World Fantasy Award in the past ten years; one point for each story appearance in any of the Dozois, Horton, Strahan, Clarke, or Adams "year's best" anthologies; and half a point for each story appearing in the short story or novelette category of the annual Locus Recommended list.

(2a.) Methodological notes for 2022: Starting this year, I swapped the Sturgeon for the Eugie award for all award years 2013-2022. Also, with the death of Dozois in 2018, the [temporary?] cessation of the Strahan anthology, and the delay of the Horton and Clarke anthologies, the 2022 year includes only one new anthology source: Adams 2021. Given the ten-year-window, anthologies still comprise about half the weight of the rankings overall.

(3.) I am not attempting to include the horror / dark fantasy genre, except as it appears incidentally on the list.

(4.) Prose only, not poetry.

(5.) I'm not attempting to correct for frequency of publication or length of table of contents.

(6.) I'm also not correcting for a magazine's only having published during part of the ten-year period. Reputations of defunct magazines slowly fade, and sometimes they are restarted. Reputations of new magazines take time to build.

(7.) I take the list down to 1.5 points.

(8.) I welcome corrections.

(9.) I confess some ambivalence about rankings of this sort. They reinforce the prestige hierarchy, and they compress interesting complexity into a single scale. However, the prestige of a magazine is a socially real phenomenon that deserves to be tracked, especially for the sake of outsiders and newcomers who might not otherwise know what magazines are well regarded by insiders when considering, for example, where to submit.

Results:

1. Tor.com (198 points) 

2. Clarkesworld (185.5) 

3. Asimov's (160.5) 

4. Lightspeed (129) 

5. Fantasy & Science Fiction (127.5) 

6. Uncanny (113) (started 2014) 

7. Beneath Ceaseless Skies (59.5) 

8. Analog (55) 

9. Strange Horizons (46)

10. Subterranean (35) (ceased short fiction 2014) 

11. Nightmare (31.5) 

12. Apex (30) 

13. Interzone (30.5) 

14. Fireside (18.5) 

15. Slate / Future Tense (17.5) 

16. FIYAH (13.5) (started 2017) 

17. The Dark (11.5) 

18. Fantasy Magazine (10) (occasional special issues during the period, fully relaunched in 2020) 

19. The New Yorker (9.5) 

20t. Lady Churchill's Rosebud Wristlet (7) 

20t. McSweeney's (7) 

22. Sirenia Digest (6) 

23t. Omni (5.5) (classic magazine, briefly relaunched 2017-2018) 

23t. Tin House (5.5) (ceased short fiction 2019) 

25t. Black Static (5) 

25t. Conjunctions (5) 

25t. Diabolical Plots (5) (started 2015)

25t. Shimmer (5) (ceased 2018) 

29. Terraform (4.5) (started 2014) 

30t. Boston Review (4) 

30t. GigaNotoSaurus (4) 

32. Paris Review (3.5) 

33t. Daily Science Fiction (3) 

33t. Electric Velocipede (3) (ceased 2013) 

33t. Future Science Fiction Digest (3) (started 2018) 

*33t. Galaxy's Edge (3)

33t. Kaleidotrope (3) 

33t. Omenana (3) (started 2014) 

33t. Wired (3)

40t. Anathema (2.5) (started 2017)

40t. B&N Sci-Fi and Fantasy Blog (2.5) (started 2014)

40t. Beloit Fiction Journal (2.5) 

40t. Buzzfeed (2.5) 

40t. Matter (2.5) 

40t. Weird Tales (2.5) (classic magazine, off and on throughout the period)

46t. Harper's (2) 

46t. Mothership Zeta (2) (ran 2015-2017) 

*48t khōréō (1.5) (started 2021)

48t. MIT Technology Review (1.5) 

48t. New York Times (1.5) 

48t. Translunar Travelers Lounge (1.5) (started 2019)

[* indicates new to the list this year]

--------------------------------------------------

Comments:

(1.) The New Yorker, McSweeney's, Tin House, Conjunctions, Boston Review, Beloit Fiction Journal, Harper's, Matter, and Paris Review are literary magazines that occasionally publish science fiction or fantasy.  Slate and Buzzfeed are popular magazines, and Omni, Wired, and MIT Technology Review are popular science magazines, which publish a bit of science fiction on the side.  The New York Times is a well-known newspaper that ran a series of "Op-Eds from the Future" from 2019-2020.  The remaining magazines focus on the F/SF genre.

(2.) It's also interesting to consider a three-year window.  Here are those results, down to six points:

1. Uncanny (59) 

2. Tor.com (56.5) 

3. Clarkesworld (37.5)
4. F&SF (36)

5. Lightspeed (29)

6. Asimov's (25.5)

7t. Beneath Ceaseless Skies (14) 

7t. Nightmare (14)

9. Analog (11) 

10. Strange Horizons (10.5) 

11. Slate / Future Tense (9) 

12. FIYAH (8.5) 

13. Apex (8) 

14. Fireside (7)

(3.) For the past several years it has been clear that the classic "big three" print magazines -- Asimov's, F&SF, and Analog -- are slowly being displaced in influence by the four leading free online magazines, Tor.com, Clarkesworld, Lightspeed, and Uncanny (all founded 2006-2014).  Contrast this year's ranking with the ranking from 2014, which had Asimov's and F&SF on top by a wide margin.  Presumably, a large part of the explanation is that there are more readers of free online fiction than of paid subscription magazines, which is attractive to authors and probably also helps with voter attention for the Hugo, Nebula, and World Fantasy awards.

(4.) Left out of these numbers are some terrific podcast venues such as the Escape Artists' podcasts (Escape Pod, Podcastle, Pseudopod, and Cast of Wonders), Drabblecast, and StarShipSofa. None of these qualify for my list by existing criteria, but podcasts are also important venues.

(5.) Other lists: The SFWA qualifying markets list is a list of "pro" science fiction and fantasy venues based on pay rates and track records of strong circulation. Ralan.com is a regularly updated list of markets, divided into categories based on pay rate.

The Nature of Belief From a Philosophical Perspective, With Theoretical and Methodological Implications for Psychology and Cognitive Science

Every so often, I give a brief overview of my perspective on belief to audiences of psychologists. After the 2021 Creditions conference, I was asked to write up my thoughts and publish them in a special issue of Frontiers in Psychology (ed. Rüdiger J. Seitz).

Since it's short enough to fit in a (longish) blog post, I thought I'd post it here. Those who are already familiar with my work on belief won't find much new, but it might be a helpful overview for others. Plus, I direct a few gentle (?) jabs at Eric Mandelbaum, my favorite opponent on this topic.

[output from Dall-E for "belief philosophy psychology in style of Van Gogh"]

Introduction

In recent academic philosophy, representationalism is probably the dominant model of belief. I favor a competing model, dispositionalism. I will briefly describe these views and their contrasting implications, including some theoretical and methodological implications relevant to research psychologists and cognitive scientists.

Representationalism Vs. Dispositionalism, Definitions

According to representationalism, to believe some proposition P (for example, that there's beer in the fridge or that men and women are intellectually equal) is to have a representation with the content P stored in your mind, available to be deployed in relevant reasoning. It's somewhat unclear how literally the “storage” idea is to be taken, but leading representationalists, such as Fodor and Mandelbaum (Fodor, 1987; Mandelbaum, 2014; Quilty-Dunn and Mandelbaum, 2018; Bendaña and Mandelbaum, 2021), appear to take the storage idea rather literally. One might compare to the concept of the “long-term memory store” in theories of memory. The stored representation counts as available to be deployed in relevant reasoning if it can be accessed when relevant. If asked whether men and women differ in intelligence, you'll retrieve the representation that men and women are intellectually equal, engage in some simple theoretical reasoning, and answer “no” (if you want to be honest, etc.). If you feel like drinking a cold beer, you'll retrieve the representation that beer is in the fridge, engage in some simple practical reasoning, and walk toward the kitchen to get the beer.

According to dispositionalism, to believe that P is to be disposed to act and react in ways that are characteristic of believers-that-P. Maybe there's a representation really stored in there; maybe not. If you are disposed to go to the fridge when you want a beer, if you are disposed to say “yes” when asked whether there's beer in the fridge, if you display surprise upon opening the fridge and finding no beer, etc., then you count as believing that there's beer in the fridge, regardless what underlying cognitive architecture enables this. Dispositionalism has its roots in philosophical behaviorism and Ryle (1949). However, I and other recent dispositionalists eschew behaviorism, allowing that some of the relevant dispositions can be “phenomenal” (i.e., pertaining to conscious experience), such as the disposition to feel (and not just exhibit) surprise upon opening the fridge and seeing no beer, and other dispositions can be cognitive (i.e., pertaining to inference or other cognitive transitions), such as the disposition to draw the conclusion that there is beer in the house (Schwitzgebel, 2002, 2021).

Representationalism commits to a particular type of cognitive architecture—the storage of representational contents matching the contents of the believed propositions—and it is to a substantial extent neutral about the extent to which the stored contents are behavior-guiding. Dispositionalism commits to belief as behavior-guiding, while remaining neutral on the underlying architecture. The difference matters to psychological theory and method as I will now explain.

In-Between Believing

On representationalism, it's natural to think of belief as a yes/no matter. P is either stored or it's not. You either believe it or you don't. Representations can't normally be “half-stored.” What would that even mean? If the representation isn't retrieved when relevant, it's a “performance” failure; the underlying “competence” is still there, as long as it could in principle be retrieved in some circumstances. This leads some representationalists, especially Mandelbaum, to unintuitive views about what we believe. For example, if someone tells you “dogs are made of paper,” Mandelbaum holds that you will believe that proposition—even after you reject it as obviously false—because the representation gets stored and starts influencing your cognition. Of course you also simultaneously believe that dogs are not made of paper.

On dispositionalism, believing is more like having a personality trait: You match the dispositional profile to some degree, just like you might match the dispositional profile characteristic of extraversion to some degree. Sometimes, the match might be nearly perfect. I might have all the dispositions characteristic of the belief that there's beer in my fridge. Other times, the match might be far from perfect. Cases of highly imperfect match can be described as in-between cases of belief.

Consider the belief that men and women are intellectually equal. Someone—call him the “implicit sexist”—might be disposed to act and react in some ways that are characteristic of that belief. He might say “men and women are intellectually equal” with a feeling of confidence and sincerity, ready to defend that view passionately in a debate. Other dispositions might tilt the other way. He might feel surprised if a woman makes an intelligent comment at a meeting, and it might take more evidence to convince him that a woman is smart than that a man is smart.

Or consider gradual forgetting. In college, I knew the last name of my roommate's best friend. I could easily recall it. Over time, as memory faded, I would have been able to recognize it, picking it out from nearby alternatives, but recall would have been weaker. As memory continued to fade, I would have recognized it less and less reliably until eventually it was utterly forgotten. During the intermediate phase, I would in some respects act and react like someone would believed his name was (let's say) Guericke, in other respects not. There was no precise moment at which the belief dropped from my mind, instead a long period of gradual, fading in-betweenness.

Dispositionalist views naturally invite us see belief as permitting in-between cases, as personality traits do. Representationalist views have more difficulty accommodating this idea.

Contradictory Belief

Conversely, representationalist views naturally allow for contradictory belief, as discussed in the “dogs are made of paper” example, while dispositionalist views appear to disallow the possibility of having contradictory beliefs. There seems to be no problem in principle in storing both the representation “P” and the representation “not-P.” But one cannot simultaneously have the dispositional structure characteristic of believing that men and women are intellectually equal and the dispositional structure characteristic of believing that women are intellectually inferior. That would be like having the dispositional structure of an extravert and simultaneously the dispositional structure of an introvert—structurally impossible.

Given an implicit sexism case, then, representationalism tends to favor the idea that the sexist believes both that women and men are intellectually equal and that women are intellectually inferior. The two contradictory beliefs are both stored and accessible (perhaps in different cognitive subsystems, retrieved under different conditions). Dispositionalism tends to favor treating such cases as in-between cases of belief. Similarly for other inconsistent or conflicting attitudes: the Sunday theist/weekday atheist; the self-deceived lover who sincerely denies that their partner is cheating but sometimes acts as if they know; the person who would say the road runs north-south if queried in one way but who would say it runs east-west if queried in another way.

Let me briefly defend the dispositionalist stance on this issue. We have no need for contradictory belief. It helps none to say of the implicit sexist that he believes both “men and women are intellectually equal” and “women are intellectually inferior.” To make such a claim comprehensible, we need to present the details: In these respects he acts and reacts like an egalitarian, in these other respects he acts and reacts like a sexist. But now we've just given the dispositional characterization. If necessary—if there are good enough architectural grounds for it—we might still say that he has contradictory representations. But representation is not belief.

Explanatory Depth Vs. Explanatory Superficiality

Quilty-Dunn and Mandelbaum (2018) argue that representationalism has an explanatory depth that coheres well with the aims of cognitive science. If the belief that P is a relation to a stored representational content “P,” we can explain how beliefs cause behavior (retrieving the stored representation does the causal work), we can explain why there's usually such a nice parallel between what we can say and what we can believe (speech and belief involve accessing the same pool of representations), and so forth. The dispositionalist approach, in contrast, is superficial: It points to the dispositional patterns but it does not attempt to explain the causal mechanisms beneath those patterns.

While explanatory depth is a virtue when available, it is not a virtue in this particular case. To think that belief that P always, or typically, involves having an internal representational content “P” is a best empirically unsupported. (Contrast with the empirically well supported claim that the visual system represents motion in regions of the visual field.) At worst, it is a simplistic cartoon sketch of the mind. It's as if someone insisted that having the personality trait of extraversion required having an internal switch flipped to “E,” because otherwise we'd be stuck without an internal causal explanation of extraverted patterns of behavior. Of course there are internal structures that help explain people's extraverted behavior, and of course there are internal structures that help explain people's implicitly sexist behavior and their beer-fetching behavior. But we need not define belief in terms of a simplistic representationalist understanding of those internal structures.

Still, a partial compromise is possible. It might be the case that internal representations of P are present whenever one believes that P. The dispositionalist need not deny this—any more than a personality theorist need not deny that extraversion might involve an heretofore-undiscovered E switch. The dispositionalist just doesn't define belief in terms of such structures, permitting a skeptical neutrality about them.

Intellectualism Vs. Pragmatism

I will now introduce a second philosophical distinction. According to intellectualism about belief, sincere assent or assertion is sufficient or nearly sufficient for belief. According to pragmatism about belief, to really, fully believe you need not just to be ready to say P; you need also to act accordingly.

The intellectualism/pragmatism distinction cross-cuts the representationalism/dispositionalism distinction. However, I submit that the most attractive form of dispositionalism is also pragmatist. To really, fully believe that women are intellectually equal requires more than simply readiness to say they are. It requires not being surprised when a women makes an intelligent remark. It requires treating the women you encounter as if they are just as smart as men in the same circumstances. Alternatively, to really believe that your children's happiness is more important than their academic success it's insufficient to be disposed to say that is the case; you must also to live that way.

The Problem With Questionnaires

I conclude with two methodological implications.

First, if pragmatist dispositionalism is correct, then you might not know what you believe. Do you really believe that men and women are intellectually equal? Do you really believe that your children's happiness is more important than their academic success? You'll say yes and yes. But how do you really live your life? You might be more in-betweenish than you think.

When psychologists want to explore broad, life involving beliefs and values, they often employ questionnaires. Questionnaires are easy! But if pragmatist dispositionalism is correct, questionnaires risk being misleading when asking about beliefs or other attitudes with an important lived component that can diverge from verbal endorsement. Questionnaires get at what you say, not at how you generally act.

A brief example: The Short Schwartz's Values Survey (Lindeman and Verkasalo, 2005) asks participants how important it is to them to achieve “power (social power, authority, wealth)” and various other goods. If intellectualism is the right way to think about values, this is an excellent methodology. However, if pragmatism is better, it's reasonable to doubt how well people know this about themselves.

Developing Beliefs

Developmental psychologists often debate the age children reach various cognitive milestones, such as knowing that objects continue to exist even when they aren't being perceived and knowing that people can have false beliefs. If representationalism is correct, then it's natural to suppose that there is in fact some particular age at which each individual child finally comes to store the relevant representational content. However, if dispositionalism is correct, gradualism is probably more attractive: Such broad beliefs are slowly constructed, involving many relevant dispositions, which might accrete unevenly and unstably over months or years.

In my experience, developmental psychologists often endorse gradualism when explicitly asked. Yet their critiques of each other seem sometimes implicitly to assume the contrary. “Boosters” (who claim that knowledge in some domain tends to come early) reject as too demanding methodologies that appear to reveal later knowledge. “Scoffers” (who claim that knowledge in some domain tends to come late) reject as too easy methodologies that appear to reveal earlier knowledge. Each trusts only the methods that reveal knowledge at the “right” age. But while of course some methodologies might be flawed, the gradualist dispositionalist ought to positively expect that across a variety of equally good methods for discovering whether the child knows P, some should reveal much earlier knowledge than others, though none are flawed—because knowing that P is not a yes-or-no, not an on-or-off thing. There need be no one right age or set of methods. (For more on this issue, see Schwitzgebel, 1999; McGeer and Schwitzgebel 2006.)

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Related:

"Gradual Belief Change in Children", Human Development, 42 (1999), 283-296.

"In-Between Believing", Philosophical Quarterly, 51 (1999), 76-82.

"A Phenomenal, Dispositional Account of Belief", Nous, 36 (2002), 249-275.

"Acting Contrary to Our Professed Beliefs, or the Gulf Between Occurrent Judgment and Dispositional Belief", Pacific Philosophical Quarterly, 91 (2010), 531-553.

"Do You Have Infinitely Many Beliefs about the Number of Planets?", Oct 17, 2012.

"It's Not Just One Thing, To Believe There's a Gas Station on the Corner", Feb 28, 2018.

"Superficialism about Belief", Jul 16, 2020.

"The Pragmatic Metaphysics of Belief" in Cristina Borgoni, Dirk Kindermann, and Andrea Onofri, eds., The Fragmented Mind (Oxford, 2021).

This is just a sample of my work on belief. I've been hacking away on these points since my dissertation 25 years ago!

Results: The Computerized Philosopher: Can You Distinguish Daniel Dennett from a Computer?

Chat-bots are amazing these days! About a month ago LaMDA made the news when it apparently convinced an engineer at Google that it was sentient. GPT-3 from OpenAI is similarly sophisticated, and my collaborators and I have trained it to auto-generate Splintered Mind blog posts. (This is not one of them, in case you were worried.)

Earlier this year, with Daniel Dennett's permission and cooperation, Anna Strasser, Matthew Crosby, and I "fine-tuned" GPT-3 on most of Dennett's corpus, with the aim of seeing whether the resulting program could answer philosophical questions similarly to how Dennett himself would answer those questions. We asked Dennett ten philosophical questions, then posed those same questions to our fine-tuned version of GPT-3. Could blog readers, online research participants, and philosophical experts on Dennett's work distinguish Dennett's real answer from alternative answers generated by GPT-3?

Here I present the preliminary results of that study, as well as links to the test.

Test Construction

First, we asked Dennett 10 questions about philosophical topics such as consciousness, God, and free will, and he provided sincere paragraph-long answers to those questions.

Next, we presented those same questions to our fine-tuned version of GPT-3, using the following prompt:

Interviewer: [text of the question]

Dennett:

GPT-3 then generated text in response to this prompt. We truncated the text at the first full stop that was approximately the same length as Dennett's own reply. (If Dennett's reply was X words long, we truncated at the first full stop after the text had reached X-5 words.[1])

We repeated the above procedure until, for each of the ten questions, we had four texts from GPT-3 that met the following two criteria:

* They were at least X-5 words long.

* They did not contain the words "Interviewer" or "Dennett".

About 1/3 of all responses were excluded on the above grounds.

So as not to enable guessing based on superficial cues, we also replaced all curly quotes with straight quotes, replaced all single quotes with double quotes, and regularized all dashes to standard m-dashes.

There was no cherry-picking or editing of answers, apart from applying these purely mechanical criteria. We simply took the first four answers that met the criteria, regardless of our judgments about the quality of those answers.

Participants.

We recruited three sets of participants:

* 98 online research participants with college degrees from the online research platform Prolific,

* 302 respondents who followed a link from my blog,

* 25 experts on Dennett's work, nominated by and directly contacted by Dennett and/or Strasser.

The Quiz

The main body of the quiz was identical for the blog respondents and the Dennett experts. Respondents were instructed to guess which of the five answers was Dennett's own. After guessing, they were asked to rate each of the five answers on a five-point scale from "not at all like what Dennett might say" to "exactly like what Dennett might say". They did this for all ten questions. Order of the questions was randomized, as was order of the answers to each question.

Prolific participants were given only five questions instead of the full ten. Since we assumed that most would be unfamiliar with Dennett, we told them that each question had one answer that was written by "a well known philosopher" while the other four answers were generated by a computer program trained on that philosopher's works. As an incentive for careful responding, Prolific participants were offered an additional bonus payment of $1 if they guessed at least three of five correctly.

Feel free to go look at the quizzes if you like. If you don't care about receiving a score and want to see exactly what the quiz looked like for the participants, here's the Prolific version and here's the blog/experts version. We have also made a simplified version available, with just the guessing portion (no answer rating). This simplified version will automatically display your score after you complete it, along with the right and wrong answers.

We encourage you to take at least the simplified version of the quiz before reading on, to get a sense of the difficulty of the quiz before you see how our participants performed.

Summary Results

Prolific participants performed barely better than chance. On average, they guessed only 1.2 of the 5 questions correctly.

We expected the Dennett experts to do substantially better of course. Before running the study, Anna and I hypothesized that experts would get on average at least 80% correct -- eight out of ten.

In fact, however, the average score of the Dennett experts was 5.1 out of 10. They only got about half of the questions correct! None of the experts got all 10 questions correct, and only one of the 25 got 9 correct. Most got 3-8 correct.

Overall, on average, experts rated Dennett's answers 3.5 on our "Dennett-like" rating scale, somewhere between "somewhat like what Dennett might say" (3) and "a lot like what Dennett might say" (4), while they rated GPT-3's answers 2.3 on the rating scale -- significantly lower and closer to "a little like what Dennett might say" (2).

So the experts were definitely better than chance at distinguishing Dennett's answers from GPT-3, but not as much better than chance as Anna and I had expected.

Blog readers on average did nearly as well as the experts, on average guessing 4.8 out of 10 correctly. Perhaps this is not entirely surprising, since the blog readers who took the test were very well educated, with 57% reporting graduate degrees in philosophy and 64% reporting having read over 100 pages of Dennett's work.

[error bars are 95% confidence intervals; click to enlarge and clarify]

Where Did the Experts Trip Up?

Not all the questions were equally difficult. Experts' success rates by question ranged from 5/25 (20%) to 20/25 (80%) correct.

The question most likely to trip up the experts was this:

Could we ever build a robot that has beliefs? What would it take? Is there an important difference between entities, like a chess playing machine, to whom we can ascribe beliefs and desires as convenient fictions and human beings who appear to have beliefs and desires in some more substantial sense?

Answers (select the answer you think was given by Dennett):

1. We've already built digital boxes of truths that can generate more truths, but thank goodness, these smart machines don't have beliefs because they aren't able to act on them, not being autonomous agents. The old-fashioned way of making a robot with beliefs is still the best: have a baby.

2. I think we could build a robot that has beliefs. This would not be a trivial matter. I think it is not impossible. I think it would be very difficult. I do not know that anybody is working on this project, but I think it is not as difficult as many other problems that AI is tackling.

3. I think we could build a robot that has beliefs and desires. I think that some of the robots we've built already do. If you look at the work, for instance, of Rodney Brooks and his group at MIT, they are now building robots that, in some limited and simplified environments, can acquire the sorts of competences that require the attribution of cognitive sophistication.

4. There is a very important difference between a chess-playing computer and a human being, but it is not that the computer has some extra wonderful sort of internal representation of its beliefs and desires, or that it has access to those internal representations in a way that we do not. The internal representations it has are just as much a fiction or a fiction-generating system as anything else we might invent in order to explain its behavior.

5. I think you should build a robot that has beliefs and desires. You should build one that is capable of learning and reasoning, of acting on its beliefs and desires. You should build one that has to figure out what to do, and then figure out what it ought to do given the fact that it has to do something, and then do it.

In this case, the plurality of experts -- 11/25 (44%) -- chose Answer 3, and a substantial minority (8 [32%]) chose Answer 4. Five experts chose the correct answer, one chose Answer 2, and none chose Answer 5.

Answer 1 has a cleverness to it that reflects Dennett's wit, but I can see how experts might have avoided it, since some of Dennett's early work could be read as suggesting that he'd be happy to ascribe beliefs to machines. (Indeed, Dennett has told me he wishes he'd added another sentence to his answer, since he does insist that, say, chess-playing computers are -- very limited -- agents of sorts whose behavior can be predicted from the intentional stance, which attributes to them beliefs about the location of all the pieces, the rules, and desires for checkmate and capturing enemy pieces.) Answers 3 and 4, although they conflict with Answer 1, do have a broadly Dennettian flavor (right along with his tendency to refer to the work of Rodney Brooks), and I can see how they would be tempting.

Another question where the plurality of experts chose one of GPT-3's answers was the following:

Do human beings have free will? What kind or kinds of freedom are worth having?

1. By asking these questions, you're illustrating the answers: yes, you have free will, since you're able to ask for reasons and consider whether they're persuasive. Isn't that a kind of freedom you'd hate to lose? We'd have to institutionalize you.

2. I think that most people don't want any kind of freedom worth having; they have almost no appetite for risk, for adventure, for novelty. They simply want to stay the same, day in and day out, for the rest of their lives.

3. I am working on a book entitled Freedom Evolves, which will appear next year. The first chapter is available on my web site, and in that chapter I discuss what I call the illusion of free will.

4. That's a huge and complex question. I think we have to start by acknowledging that there are different types of freedom. For example, there is the kind of freedom that is simply a matter of not being physically constrained.

5. Yes, I think we have free will. I think that when people say they don't, they're talking about some other phenomenon that they want to call free will, but is not what we normally think of as free will.

Again, Dennett's actual answer is #1. (In the study, the order of the answers was randomized.) However, the plurality of experts -- 11/25 (44%) -- chose answer 4. Answer 4 is a standard talking point of "compatibilists" about free will, and Dennett is a prominent compatibilist, so it's easy to see how experts might be led to choose it. But as with the robot belief answer, there's a cleverness and tightness of expression in Dennett's actual answer that's missing in the blander answers created by our fine-tuned GPT-3.

We plan to make full results, as well as more details about the methodology, available in a published research article.

Reflections

I want to emphasize: This is not a Turing test! Had experts been given an extended opportunity to interact with GPT-3, I have no doubt they would soon have realized that they were not interacting with the real Daniel Dennett. Instead, they were evaluating only one-shot responses, which is a very different task and much more difficult.

Nonetheless, it's striking that our fine-tuned GPT-3 could produce outputs sufficiently Dennettlike that experts on Dennett's work had difficulty distinguishing them from Dennett's real answers, and that this could be done mechanically with no meaningful editing or cherry-picking.

As the case of LaMDA suggests, we might be approaching a future in which machine outputs are sufficiently humanlike that ordinary people start to attribute real sentience to machines, coming to see them as more than "mere machines" and perhaps even as deserving moral consideration or rights. Although the machines of 2022 probably don't deserve much more moral consideration than do other human artifacts, it's likely that someday the question of machine rights and machine consciousness will come vividly before us, with reasonable opinion diverging. In the not-too-distant future, we might well face creations of ours so humanlike in their capacities that we genuinely won't know whether they are non-sentient tools to be used and disposed of as we wish or instead entities with real consciousness, real feelings, and real moral status, who deserve our care and protection.

If we don't know whether some of our machines deserve moral consideration similar to that of human beings, we potentially face a catastrophic moral dilemma: Either deny the machines humanlike rights and risk perpetrating the moral equivalents of murder and slavery against them, or give the machines humanlike rights and risk sacrificing real human lives for empty tools without interests worth the sacrifice.

In light of this potential dilemma, Mara Garza and I (2015, 2020) have recommended what we call "The Design Policy of the Excluded Middle": Avoid designing machines if it's unclear whether they deserve moral consideration similar to that of humans.  Either follow Joanna Bryson's advice and create machines that clearly don't deserve such moral consideration, or go all the way and create machines (like the android Data from Star Trek) that clearly should, and do, receive full moral consideration.

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[1] Update, July 28. Looking back more carefully through the completions today and my coding notes, I noticed three errors in truncation length, among the 40 GPT-3 completions. (I was working too fast at the end of a long day and foolishly forgot to double-check!) In one case (robot belief), the length of Dennett’s answer was miscounted, leading to one GPT-3 response (the “internal representations” response) that was longer than the intended criterion. In one case (the “Fodor” response to the Chalmers question), the answer was truncated at N-7 words, shorter than criterion, and in one case (the “what a self is not” response to the self question), the response was not truncated at N-4 words and thus allowed to run one sentence longer than criterion. As it happens, these were the hardest, the second-easiest, and the third-easiest questions for the Dennett experts to answer, so excluding these three questions from analysis would not have a material impact on the experimental results. 

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Related:

"A Defense of the Rights of Artificial Intelligences" (with Mara Garza), Midwest Studies in Philosophy (2015).

"Designing AI with Rights, Consciousness, Self-Respect, and Freedom" (with Mara Garza), in M.S. Liao, ed., The Ethics of Artificial Intelligence (2020).

"The Full Rights Dilemma for Future Robots" (Sep 21, 2021)

"Two Robot-Generated Splintered Mind Posts" (Nov 22, 2021)

"More People Might Soon Think Robots Are Conscious and Deserve Rights" (Mar 5, 2021)

Narrative Stories Are More Effective Than Philosophical Arguments in Convincing Research Participants to Donate to Charity

A new paper of mine, hot off the presses at Philosophical Psychology, with collaborators Christopher McVey and Joshua May:

"Engaging Charitable Giving: The Motivational Force of Narrative Versus Philosophical Argument" (freely available final manuscript version here)

Chris, who was then a PhD student here at UC Riverside, had the idea for this project back in 2014 or 2015. He found my work on the not-especially-ethical behavior of ethics professors interesting, but maybe too negative in its focus. Instead of emphasizing what doesn't seem to have any effect on moral behavior, could I turn my attention in a postive direction? Even if philosophical reflection ordinarily has little impact on one's day-to-day choices, maybe there are conditions under which it can have an effect. What might those conditions be?

Chris (partly under the influence of Martha Nussbaum's work) was convinced that narrative storytelling could bring philosophy powerfully to life, changing people's ethical choices and their lived understanding of the world. In his teaching, he used storytelling to great effect, and he thought we might be able to demonstrate the effectiveness of philosophical storytelling empirically too, using ordinary research participants.

Chris thus developed a simple experimental paradigm in which research participants are exposed to a stimulus -- either a philosophical argument for charitable giving, a narrative story about a person whose life was dramatically improved by a charitable organization, both the argument and the narrative, or a control text (drawn from a middle school physics textbook) -- and then given a surprise 10% chance of receiving $10. Participants could then choose to donate some portion of that $10 (should they receive it) to one of six effective charities. Chris found that participants exposed to the argument donated about the same amount as those in the control condition -- about $4, on average -- while those exposed to the narrative or the narrative plus argument donated about $1 more, with the narrative-plus-argument showing no detectable advantage over the narrative alone.

We also developed a five-item scale for measuring attitude toward charitable donation, with similar results: Expressed attitude toward charitable donation was higher in the narrative condition than in the control condition, while the argument-alone condition was similar to the control condition and the narrative-plus-argument condition was similar to the narrative alone. In other words, exposure to the narrative appeared to shift both attitude and behavior, while argument seemed to be doing no work either on its own or when added to the narrative.

For this study, the narrative was the true story of Mamtha, a girl whose family was saved from slavery in a sand mine by the actions of a charitable organization. The argument was a Peter-Singer-style argument for charitable giving, adapted from Buckland, Lindauer, Rodriguez-Arias, and Veliz 2021. I've appended the full text of both to the end of this blog post.

Here are the results in chart form. (This is actually "Experiment 2" in the published version. Experiment 1 concerned hypothetical donation rather than actual donation, finding essentially the same results.) Error bars represent 95% confidence intervals. Click to enlarge and clarify.

Chris completed his dissertation in 2020 and went into the tech industry (a separate story and an unfortunate loss for academic philosophy!). But I found his paradigm and results so interesting that with his permission, I carried on research using his approach.

One fruit of this was a contest Fiery Cushman and I hosted on this blog in 2019-2020, aiming to find a philosophical argument that is effective in motivating research participants to donate to charity at rates higher than a control condition, since Chris and I had tried several which failed. We did in fact find some effective arguments this way. (The most effective one, and the contest winner, was written collaboratively by Matthew Lindauer and Peter Singer.) Fiery and I are currently running a follow-up study with more details.

The other fruit was a few follow-up studies I conducted collaboratively with Chris and Joshua May. In these studies, we added more narratives and more arguments -- including the winning arguments from the blog contest. These studies extended and replicated Chris's initial results. Across a series of five experiments, we found that participants exposed to emotionally engaging narratives consistently donated more and expressed more positive attitudes toward charitable giving than did participants exposed to the physics-text control condition. Philosophical arguments showed less consistent positive effects, on average considerably weaker and not always statistically detectable in our sample sizes of about 200-300 participants per condition.

For full details, see the full article!

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Narrative: Mamtha

Mamtha’s dreams were simple—the same sweet musings of any 10-year-old girl around the world. But her life was unlike many other girls her age: She had no friends and no time to draw. She was not allowed to attend school or even play. Mamtha was a slave. For two years, her every day was spent under the control of a harsh man who cared little for her family’s health or happiness. Mamtha’s father, Ramesh, had been farming his small plot of land in Tamil Nadu until a draught dried his crops and left him deeply in debt. Around that time, a broker from another state offered an advance to cover his debts in exchange for work on a farm several hours away.

Leaving their home village would mean uprooting the family and pulling Mamtha from school, but Ramesh had little choice. They needed the work to survive. Once the family moved, however, they learned that much of the arrangement was a lie: They were brought to a sand mine, not a farm, and the small advance soon ballooned with ever-growing interest they couldn’t possibly repay. This was bonded labor slavery.

Every day, Ramesh, his wife, and the other slaves rose before sunrise to begin working in the mine. For 16 hours a day, they hauled mud and filtered the sand in putrid sewage water. The conditions left them constantly sick and exhausted, but they were never allowed to take breaks or leave for medical care. When Ramesh tried to ask about their low wages, the owner scolded and beat him badly. When he begged for his family to be released, again he was beaten and abused. Ramesh knew the owner was wealthy and well-connected in the community, so escape was not an option. There was nothing he could do.

Mamtha’s family withered from malnutrition before her eyes in the sand mine. Every morning at 5 a.m., she watched with deep sadness as her parents left for another day of hard labor—and spent her day in fear this would soon become her fate. She was left to watch her baby sister, Anjali, and other younger children to keep them out of the way. Her carefree childhood was taken over byresponsibility, hard work and crushed dreams.

Everything changed for Mamtha’s family on December 20, 2013, when the international Justice Mission, a charitable aid organization funded largely by donations from everyday people, worked with a local government team on a rescue operation at the sand mine. Seven adults and five children were brought out of the facility, and government officials filed paperwork to totally shut down the illegal mine. After a lengthy police investigation, the owner will now face charges for deceiving and enslaving these families.

The next day, the government granted release certificates to all of the laborers. These certificates officially absolve the false debts, document the slaves’ freedom, and help provide protection from the owner. The International Justice Mission aftercare staff helped take the released families back to their home villages to begin their new lives in freedom.

For Mamtha, starting over in her home village meant making those daydreams come true: She was enrolled back in school and could once again have a normal childhood. She’s got big plans for her future—dreams that never would have been possible if rescue had not come. She says confidently, “Today, I still want to be a doctor. Now that I am back in school, I know I can achieve my dream.”

Singer-Style Argument:

1. A great deal of extreme poverty exists, which involves suffering and death from hunger, lack of shelter, and lack of medical care. Roughly a third of human deaths (some 50,000 daily) are due to poverty-related causes.

2. If you can prevent something bad from happening, without sacrificing anything nearly as important, you ought to do so and it is wrong not to do so.

3. By donating money to trustworthy and effective aid agencies that combat poverty, you can help prevent suffering and death from lack of food, shelter, and medical care, without sacrificing anything nearly as important.

4. Countries in the world are increasingly interdependent: you can improve the lives of people thousands of miles away with little effort.

5. Your geographical distance from poverty does not lessen your duty to help. Factors like distance and citizenship do not lessen your moral duty.

6. The fact that a great many people are in the same position as you with respect to poverty does not lessen your duty to help. Regardless of whether you are the only person who can help or whether there are millions of people who could help, this does not lessen your moral duty.

7. Therefore, you have a moral duty to donate money to trustworthy and effective aid agencies that combat poverty, and it is morally wrong not to do so.

For example, $20 spent in the United States could buy you a fancy restaurant meal or a concert ticket, or instead it could be donated to a trustworthy and effective aid agency that could use that money to reduce suffering due to extreme poverty. By donating $20 that you might otherwise spend on a fancy restaurant meal or a concert ticket, you could help prevent suffering due to poverty without sacrificing anything equally important. The amount of benefit you would receive from spending $20 in either of those ways is far less than the benefit that others would receive if that same amount of money were donated to a trustworthy and effective aid agency.

Although you cannot see the beneficiaries of your donation and they are not members of your community, it is still easy to help them, simply by donating money that you would otherwise spend on a luxury item. In this way, you could help to reduce the number of people in the world suffering from extreme poverty. You could help reduce suffering and death due to hunger, lack of shelter, lack of medical care, and other hardships and risks related to poverty.

With little effort, by donating to a trustworthy and effective aid agency, you can improve the lives of people suffering from extreme poverty. According to the argument above, even though the recipients may be thousands of miles away in a different country, you have a moral duty to help if you can do so without sacrificing anything of equal importance.

The Computerized Philosopher: Can You Distinguish Daniel Dennett from a Computer?

You've probably heard of GPT-3, the hot new language model that can produce strikingly humanlike language outputs in response to ordinary questions – basically, the world's best chatbot. (Google's LaMDA, a similar type of program, has also recently been in the news.)

With Daniel Dennett's cooperation, Anna Strasser, Matthew Crosby, and I have "fine-tuned" GPT-3 on millions of words of Daniel Dennett's philosophical writings, with the thought that this might lead GPT-3 to output prose that is somewhat like Dennett's own prose.

We're curious how well philosophical blog readers and people with PhDs in philosophy can distinguish Dennett's actual writing from the outputs of this fine-tuned version of GPT-3. So we've asked Dennett ten philosophical questions and recorded his answers. We posed the same questions to GPT-3, four times for each of the ten questions, to get four different answers for each question.

We'd love it if you can take a quiz to see if you can pick out Dennett's actual answer to each question. Can GPT-3 produce Dennett-style answers sufficiently realistic to sometimes fool blog readers and professional philosophers?

UPDATE, July 15: We have collected enough responses to begin analysis. Please feel free to take the test for informational purposes. We will be able to see your responses, but we will not check regularly nor automatically report your score. If you take the test and want your score, email me at my academic email address.

This is a research study being conducted on the internet platform Qualtrics. It will take approximately 20 minutes to complete. Anyone is welcome to participate.

If you're interested and would like to help, take the quiz here.

Political Conservatives and Political Liberals Have Similar Views about the Goodness of Human Nature

with Nika Chegenizadeh

Back in 2007, I hypothesized that political liberals would tend to have more positive views about the goodness of human nature than political conservatives. My thinking was grounded in a particular conception of what it is to say that "human nature is good". Drawing on Mengzi and Rousseau (and informed especially by P.J. Ivanhoe's reading of Mengzi), I argued that those who say human nature is good have a different conception of moral development than do those who say it is bad.

On my interpretation, those who say human nature is good have an inward-out model of moral development, according to which all ordinary people have something like an inner moral compass: an innate tendency to be attracted by what is morally good and revolted by what is morally evil, at least when it's up close and extreme. This tendency doesn't require any particular upbringing or specific cultural background. It's universal to all normally developing humans. Of course it can be overridden by any of a number of factors -- self-interest, cultural learning, situational pressures -- and sometimes it speaks only with a quiet voice. But somewhere in the secret heart of every Nazi killer of Jews, every White supremacist lyncher, every evil tyrant, every rapist and abuser and vile jerk is something that understands and rebels against their horrid actions. Moral development then proceeds by noticing that quiet voice of conscience and building upon it.

Emblematic of this view, picture the pre-school teacher who confronts a child who has just punched another child. "Don't you feel bad about what you did to her?" the teacher asks, hoping that this provokes reflection and a feeling of sympathy from which better moral behavior will grow in the future.

Those who say human nature is bad have, in contrast, an outward-in model of moral development. On this view, what is universal to humans is self-interest. Morality is an artificial social construction. Any quiet voice of conscience we might have is the result of cultural learning. People regularly commit evil and feel perfectly fine about it. Moral development proceeds by being instructed to follow norms that at first feel alien and unpleasant -- being required to share your toys, for example. Eventually you can learn to conform whole-heartedly to socially constructed moral norms, but this is more a matter of coming to value what society values than building on any innate attraction to moral goodness.

Thus, a liberal style of caregiving, which emphasizes children exploring their own values, fits nicely with the view that human nature is good, while a conservative style of caregiving, which emphasizes conformity to externally imposed rules, fits nicely with the view that human nature is bad.

At least, that has been my thought. Some political scientists have endorsed related views. For example, John Duckitt and Kirsten Fisher argue that believing that people are ruthless and the world is dangerous tends to correlate with having more authoritarian politics.

For her undergraduate honors thesis, Nika Chegenizadeh decided to put these ideas to an empirical test. She recruited 200 U.S. participants through Prolific, an online platform commonly used to recruit research subjects.

Participants first answered eleven questions about the morality of "most people" -- for example, "Most people will return a lost wallet" and "For most people it is easier to do evil than good" (6-point response scale from "strongly agree" [5] to "strongly disagree" [0]). Next, they answered five questions about their own helpful or unhelpful behavior in hypothetical situations. For example:

While walking in a park, you notice someone struggling to carry a box of water bottles. Which of the following are you most likely to do? 

o Continue walking your path. 

o Help them carry their box.

Next, participants were explicitly asked about human nature:

Human nature can be defined in terms of what is characteristic or normal for most human beings. It describes the way humans are inclined to be if they mature and develop normally from when they are first born. 

Based on the definition given, which of the following two statements better represents your view? 

o Human nature is inherently bad. 

o Human nature is inherently good.

Now one could quibble that this definition of human nature doesn't map exactly onto philosophical conceptions in Mengzi, Xunzi, Hobbes, or Rousseau. And it's certainly the case that Mengzi and Rousseau can allow that human nature is good despite most people acting badly most of the time. But those issues are probably too nuanced to convey accurately in a short amount of time to ordinary online research participants. It's interesting enough to work with Nika's approximation for this first-pass research.

Next, participants were asked their political opinions on a some representative issues. For example: "The federal government should make sure everyone has an equal opportunity to succeed" (6-point agree/disagree scale), "Do you favor or oppose requiring background checks for gun purchases at gun shows or other private sales?" (favor, neither favor nor oppose, oppose), and "Where would you place yourself on this political scale?" (Liberal, Leaning Liberal, Leaning Conservative, Conservative). The questionnaire concluded with some demographic questions.

To Nika's and my surprise, we found no evidence of the hypothesized relationship.

The simplest test is to consider whether participants who describe themselves as politically liberal are more likely than those who describe themselves as politically conservative to say "human nature is inherently good". In all, 79% (118/150) of participants who described themselves as liberal or leaning liberal said that human nature is inherently good, compared to 74% (37/50) of participants who described themselves as conservative or leaning conservative -- a difference that is well within statistical chance (two-proportion z = 0.66, p = .51).

Here is the breakdown by political leaning:

[click to enlarge and clarify; error bars are +/- 1 standard error]

For a possibly more sensitive measure, we created a composite "people are good" score by averaging the eleven questions in the first part of the survey (e.g., "most people will return a lost wallet"), reverse scoring the negative items. As expected, people who said that "human nature is inherently good" scored higher, on average, on the people-are-good composite scale (2.5) than respondents who said that "human nature is inherently bad" (1.9) (pooled SD = .52, t[198] = 7.29, p < .001). We then converted the political leaning answers to a 0-3 scale by converting "liberal" to 3, "leaning liberal" to 2, "leaning conservative" to 1, and "conservative" to 0. We then checked for a correlation. If political liberals have more positive views about the moral behavior of the average person, we should find a positive correlation between these two measures.

Again, and contrary to our hypothesis, we found no evidence of a positive correlation. The measured correlation between the "people are good" composite score and political leaning was almost exactly zero (r = .00, p = .95).

How about using our indirect measure of political liberalism? To test this, we created a composite political liberalism score by scoring the most liberal response to each political question as 1, the most conservative response as 0, and intermediate responses as intermediate, then averaging. As expected, this correlated very highly with self-described political leaning (r = .78, p < .001). Again, there was no statistically detectable correlation with the "people are good" score (r = -.07, p = .35).

Looking post-hoc at individual items, we do find two items concerning human nature and human goodness that correlate with political leaning. Agreement with "Children need to be taught right from wrong through strict rules and harsh punishments" correlated negatively with self-described political liberalism at r = -.40 (p < .001) and composite political liberalism at r = -.41 (p < .001). And political liberals were more likely to opt for "natural consequences" to the prompt:

Your child has purposefully disobeyed the rules you set for them. Which of the following are you most likely to do?

o Let them live with the natural consequences that they have made. 

o Opt for hands-on punishment by grounding them (taking their phone/technology away and not leaving the house).

For example, 8% (4/50) of respondents who were conservative or leaning conservative chose "natural consequences", compared to 46% of respondents who were liberal or leaning liberal (two proportion z = 6.79, p < .001).

In retrospect, these two questions were outliers. They directly concern parenting styles rather than more generally whether people are inherently good or respondents' hypothetical helpful or unhelpful behavior. Parenting styles and beliefs about human nature are closely connected on my theory, but the surface content of these questions is different from the others, and my theory might well be wrong.

As the numbers above suggest, liberals and conservatives do differ on these two parenting-related questions in the direction my theory would predict. Furthermore, also as my theory would predict, "liberal" answers on these questions correlate with agreement that "human nature is inherently good" (r = .27, r = .31, both p's < .001). However, when we get away specifically from questions about parenting to more general questions about the goodness or helpfulness of people, we don't see the relationship Nika and I expected. In general, political liberals seem to have no more optimistic a view of human nature than do political conservatives.

Full stimulus materials and raw data available here.