Table of Contents Foreword .................................................................................................... ......................................... xiv Preface .................................................................................................... .............................................. xv Acknowledgment .................................................................................................... .......................... xxiii Section 1 On the Cusp: Critical Appraisals of a Growing Dependency on Intelligent Machines Chapter 1 Algorithms versus Hive Minds and the Fate of Democracy ................................................................... 1 Rick Searle, IEET, USA Chapter 2 We Can Make Anything: Should We? .................................................................................................. 15 Chris Bateman, University of Bolton, UK Chapter 3 Grounding Machine Ethics within the Natural System ........................................................................ 30 Jared Gassen, JMG Advising, USA Nak Young Seong, Independent Scholar, South (...) Korea Section 2 From the Outside In: Intelligent Machine Technologies as a Window on Human Morality both as Evolved and as Evident in Internet Discourse, Today Chapter 4 The Emergence of Arti cial Autonomy: A View from the Foothills of a Challenging Climb ............. 51 Fernando da Costa Cardoso, Universidade Nova de Lisboa, Portugal Luís Moniz Pereira, Universidade Nova de Lisboa, Portugal Chapter 5 Semantic Analysis of Bloggers Experiences as a Knowledge Source of Average Human Morality .... 73 Rafal Rzepka, Hokkaido University, Japan Kenji Araki, Hokkaido University, Japan Section 3 From the Inside Out: The Ethics of Human Enhancement from Moral Perception to Competition in the Workplace Chapter 6 Machine Ethics Interfaces: An Ethics of Perception of Nanocognition ............................................... 97 Melanie Swan, Kingston University, UK Chapter 7 Ethical Concerns in Human Enhancement: Advantages in Corporate/Organizational Settings ......... 124 Ben Tran, Alliant International University, USA Section 4 From Far to Near and Near to Far: The Ethics of Distancing Technologies in Education and Warfare Chapter 8 Responsibility and War Machines: Toward a Forward-Looking and Functional Account ................. 152 Jai Galliott, Macquarie University, Australia Chapter 9 Ethical Responsibilities of Preserving Academicians in an Age of Mechanized Learning: Balancing the Demands of Educating at Capacity and Preserving Human Interactivity ................... 166 James E. Willis III, Indiana University, USA Viktoria Alane Strunk, Independent Scholar, USA Section 5 Wrapping Things Up, then Unwrapping Them Again: Integral Visions of Morality in a Technological World, Over Evolutionary Time, with Revolutionary Means, and with Open Questions about the Final Purpose of It All Chapter 10 Bridging Two Realms of Machine Ethics ........................................................................................... 197 Luís Moniz Pereira, Universidade Nova de Lisboa, Portugal Ari Saptawijaya, Universidade Nova de Lisboa, Portugal & Universitas Indonesia, Indonesia Chapter 11 Robots in Warfare and the Occultation of the Existential Nature of Violence ................................... 225 Rick Searle, IEET, USA Chapter 12 Self-Referential Complex Systems and Aristotle’s Four Causes ........................................................ 239 Aleksandar Malecic, University of Nis, Serbia Related References .................................................................................................... ........................ 261 Compilation of References .................................................................................................... ........... 292 About the Contributors .................................................................................................... ................ 325 Index .................................................................................................... ............................................... 329 . (shrink)

L’osservazione della natura con l’intento di capire l’origine della varietà di forme e fenomeni in cui si manifesta ha origini remote. All’inizio il rapporto con i fenomeni naturali era dominato da sentimenti quali paura e stupore che conducevano a supporre l’esistenza di entità sfuggenti alla percezione diretta che permeavano gli elementi animandoli. Ecco dunque che la magia rappresenta l’elemento dominante della filosofia naturale primitiva caratterizzata da una unicità degli eventi e dalla impossibilità di capirli e dominarli in quanto frutto della (...) volontà di essenze a noi estranee e non governabili. Con il nascere della civiltà ed il suo progredire il tempo dedicato ai lavori necessari per il sostentamento e la sopravvivenza diminuì e nella ripartizione dei compiti alcuni individui potevano dedicare parte del loro tempo alla osservazione della natura ed alla sua interpretazione in termini non trascendenti. Nella natura, intesa come tutto ciò che ci circonda composto da esseri viventi e da materia inorganica nelle sua varie aggregazioni sulla terra e nel cosmo, ciò che attirò l’attenzione fin dall’inizio furono furono i fenomeni regolari e periodici come i moti della luna, dei pianeti e delle stelle. Nel contempo dopo una spinta iniziale dettata da esigenze pratiche come contare gli oggetti o misurare i campi, la matematica si era sviluppata autonomamente e si rivelò idonea a descrivere in termini quantitativi i moti dei corpi celesti. La terra era al centro dell’universo mentre il moto degli altri corpi celesti risultava da una composizione di moti circolari uniformi. Questa visione geocentrica e pitagorica (armonia delle sfere) dell’universo ha prevalso fino agli albori della scienza moderna, anche se una descrizione eliocentrica, basata su validi argomenti, era stata proposta. Per quanto riguarda la struttura della materia i presocratici avevano già proposto i quattro elementi mentre gli atomisti avevano ricondotto tutto ad entità elementari primigenie, il cui aggregarsi e disgregarsi da luogo a tutti gli stati e le molteplici forme della materia. Queste intuizioni si ritrovano nella fisica moderna che contempla quattro stati di aggregazione, che hanno come unico sostrato comune gli atomi. La fisica moderna nasce con Galileo e Newton, la cui dinamica si sviluppa a partire dalle leggi di Keplero che descrivono il moto dei pianeti nel sistema eliocentrico, per potersi poi applicare ad un qualunque sistema materiale. Pertanto nei due secoli successivi si ritenne che un modello meccanico potesse essere sviluppato per un qualunque sistema fisico e quindi per l’universo intero la cui evoluzione doveva essere matematicamente prevedibile. Per i fenomeni termici tuttavia vennero formulate leggi ad hoc come quelle della termodinamica che mostrano come i processi macroscopici siano irreversibili in contrasto con le leggi della meccanica. Si deve a Boltzmann1 il tentativo di ricondurre la termodinamica alla meccanica per un gran numero di particelle dei cui moti disordinati viene data una lettura di carattere statistico. L’aumento della entropia e la irreversibilità seguono dalla ipotesi di caos molecolare ossia che i moti siano così disordinati che si perde rapidamente memoria dello stato iniziale. L’idea di introdurre una misura di probabilità nel contesto della meccanica sembra antitetica con la natura stessa della teoria rivolta fino ad allora allo studio di sistemi con moti regolari, reversibili e prevedibili individualmente su tempi lunghi. Tuttavia l’analisi probabilistica diventa essenziale per lo studio di sistemi caratterizzati da forti instabilità, e da orbite irregolari per i quali la previsione richiede una conoscenza della condizioni iniziali con precisioni fisicamente non raggiungibili. Combinando la evoluzione deterministica della meccanica di Newton o di Hamilton con la descrizione statistica attraverso una opportuna misura invariante di probabilità nello spazio delle fasi, nasce la teoria dei sistemi dinamici2 che consente di descrivere non solo i sistemi ordinati o i sistemi caotici ma anche tutti quelli che vedono coesistere in diverse proporzioni ordine e caos e che presentano una straordinaria varietà di strutture geometriche e proprietà statistiche, tanto da fornire almeno se non proprio un quadro teorico per lo meno metafore utili per la descrizione dei sistemi complessi. Anche se non c’è unanime consenso ci sembra appropriato definire complessi non tanto sistemi caratterizzati da interazioni non lineari tra i suoi componenti e da proprietà emergenti, che rientrano a pieno titolo nel quadro dei sistemi dinamici, ma piuttosto i sistemi viventi o quelli di vita artificiale che ne condividono le proprietà essenziali3. Tra queste possiamo certamente annoverare la capacità di gestire la informazione e di replicarsi, consentendo tramite un meccanismo di mutazione e selezione di dare origine a strutture di crescente ricchezza strutturale e dotate di capacità cognitive sempre più elaborate. Una teoria dei sistemi complessi non esiste ancora, anche se la teoria degli automi sviluppata da Von Neumann4 e la teoria della evoluzione di Darwin5 ne possono fornire alcuni pilastri importanti. Recentemente la teoria delle reti è stata utilizzata con successo per descrivere le proprietà statistiche delle connessioni tra gli elementi costitutivi (nodi) di un sistema complesso6. Le connessioni che non sono né completamente casuali né completamente gerarchiche, consentono una sufficiente robustezza rispetto a malfunzionamenti o danneggiamenti dei nodi unita a un adeguato livello di organizzazione per consentirne un funzionamento efficiente. Nei sistemi fisici il modello base è un insieme di atomi o molecole interagenti, che danno luogo a strutture diverse quali un gas, un liquido o un cristallo, come risultato di proprietà emergenti. Nello stesso modo per i sistemi complessi possiamo proporre un sistema automi interagenti come modello base. Le molteplici forme che il sistema assume anche in questo caso vanno considerate come proprietà emergenti del medesimo sostrato al mutare delle condizioni esterne e frutto delle i replicazioni, ciascuna delle quali introduce piccole ma significative varianti. Questa è la grande differenza tra un sistema fisico ed un sistema complesso: il primo fissate le condizioni esterne ha sempre le medesime proprietà, il secondo invece cambia con il fluire del tempo perché la sua organizzazione interna muta non solo al cambiare di fattori ambientali ma anche con il succedersi delle generazioni. C’è dunque un flusso di informazione che cresce con il tempo e che consente agli automi costituenti ed alla intera struttura di acquisire nuove capacità. Questo aumento di ordine e ricchezza strutturale avviene naturalmente a spese dell’ambiente circostante, in modo che globalmente i la sua entropia cresce in accordo con la seconda legge della termodinamica. In assenza di una teoria formalizzata paragonabile a quella dei sistemi dinamici, per i sistemi complessi si possono fare osservazioni e misure, sia puntuali sui costituenti elementari e sulle loro connessioni, sia globali sull’intero sistema, oppure costruire modelli suscettibili di essere validati attraverso la simulazione. Se di un sistema si riesce infatti a fornire una descrizione sufficientemente dettagliata, è poi possibile osservare come questo si comporti traducendo le regole in algoritmi e costruendo quindi una versione virtuale, anche se semplificata del sistema stesso. Il passaggio più difficile è il confronto tra il sistema simulato ed il sistema vero, che passa necessariamente attraverso la valutazione di una numero limitato di parametri che ne caratterizzino e proprietà. La codifica del progetto è una proprietà cruciale dei sistemi complessi perché questa si realizza con un dispendio di massa ed energia incomparabilmente più piccolo rispetto a quello necessario per realizzare l’intera struttura; nello stesso tempo apportare piccole modifiche ad un progetto è rapido ed economico. In questo processo che comporta la continua introduzione di varianti si aprono molteplici strade e con lo scorrere del tempo si realizza una storia in modo unico e irripetibile. Anche il susseguirsi di eventi fisici caratterizzati da processi irreversibili e dalla presenza di molteplici biforcazioni da origine ad una storia che non si può percorrere a ritroso, né riprodurre qualora fossimo in grado ripartire dalle stesse condizioni iniziali. Tuttavia esiste una differenza profonda tra la storia di un sistema fisico come il globo terrestre e la storia della vita. La prima registra i molteplici cambiamenti che ha subito la superficie del nostro pianeta ove montagne e mari nascono e scompaiono senza un chiaro disegno soggiacente. La storia della vita è caratterizzata da una progressiva crescita della ricchezza strutturale e funzionale e accompagnata da una crescita della complessità progettuale. La rappresentazione di questa storia prende la forma di un albero con le sue ramificazioni che mostra la continua diversificazione delle strutture e la loro evoluzione verso forme sempre più avanzate. La direzione in cui scorre il tempo è ben definita: le strutture affinano le capacità sensoriali mentre cresce la potenza degli organi che elaborano la informazione. Un sistema complesso è anche caratterizzato da un molteplicità di scale, tanto più alta quanto più si sale sulla scala evolutiva. La ragione è che il procedere verso strutture sempre più elaborate avviene utilizzando altre strutture come mattoni per cui l’immagine che si può fornire è quella di una rete di automi a più strati: partendo dal basso una rete con le sue proprietà emergenti diventa il nodo di una rete di secondo livello, cioè un automa di secondo livello che interagisce con altri automi dello stesso tipo e così via. Nei sistemi inorganici, dove non esiste un progetto, si distinguono di norma solo due livelli, quello dei costituenti elementari e quello su scala macroscopica. I sistemi fisici sono riconducibili a poche leggi universali, che governano i costituenti elementari della materia, ma il passaggio dalla descrizione dalla piccola alla grande scala è impervio e consentito soltanto dalla simulazione numerica, quando ci allontaniamo dalle situazioni più semplici caratterizzate da un equilibrio statistico. I limiti che il disegno riduzionista incontra già per i sistemi fisici diventano decisamente più forti nel caso dei sistemi complessi. (shrink)

According to the antirealist argument known as the pessimistic induction, the history of science is a graveyard of dead scientific theories and abandoned theoretical posits. Support for this pessimistic picture of the history of science usually comes from a few case histories, such as the demise of the phlogiston theory and the abandonment of caloric as the substance of heat. In this article, I wish to take a new approach to examining the ‘history of science as a graveyard of theories’ (...) picture. Using JSTOR Data for Research and Springer Exemplar, I present new lines of evidence that are at odds with this pessimistic picture of the history of science. When rigorously tested against the historical record of science, I submit, the pessimistic picture of the history of science as a graveyard of dead theories and abandoned posits may turn out to be no more than a philosophers’ myth. (shrink)

Accounts of arguments from expert opinion take it for granted that expert judgments count as (defeasible) evidence for propositions, and so an argument that proceeds from premises about what an expert judges to a conclusion that the expert is probably right is a strong argument. In Mizrahi (2013), I consider a potential justification for this assumption, namely, that expert judgments are significantly more likely to be true than novice judgments, and find it wanting because of empirical evidence suggesting that expert (...) judgments under uncertainty are not significantly more likely to be true than novice judgments or even chance. In this paper, I consider another potential justification for this assumption, namely, that expert judgments are not influenced by the cognitive biases novice judgments are influenced by, and find it wanting, too, because of empirical evidence suggesting that experts are vulnerable to pretty much the same cognitive biases that novices are vulnerable to. If this is correct, then the basic assumption at the core of accounts of arguments from expert opinion, namely, that expert judgments count as (defeasible) evidence for propositions, remains unjustified. (shrink)

It is a common view among philosophers of science that theoretical virtues (also known as epistemic or cognitive values), such as simplicity and consistency, play an important role in scientific practice. In this article, I set out to study the role that theoretical virtues play in scientific practice empirically. I apply the methods of data science, such as text mining and corpus analysis, to study large corpora of scientific texts in order to uncover patterns of usage. These patterns of usage, (...) in turn, might shed some light on the role that theoretical virtues play in scientific practice. Overall, the results of this empirical study suggest that scientists invoke theoretical virtues explicitly, albeit rather infrequently, when they talk about models (less than 30%), theories (less than 20%), and hypotheses (less than 15%) in their published works. To the extent that they are mentioned in scientific publications, the results of this study suggest that accuracy, consistency, and simplicity are the theoretical virtues that scientists invoke more frequently than the other theoretical virtues tested in this study. Interestingly, however, depending on whether they talk about hypotheses, theories, or models, scientists may invoke one of those theoretical virtues more than the others. (shrink)

In this paper, I reply to Seidel’s objections against my argument from expert performance to the effect that arguments from expert opinion are weak arguments. I clarify what Seidel takes to be unclear points in my argument and show that it withstands Seidel’s objections.

It is generally accepted among philosophers of science that hypothesis testing is a key methodological feature of science. As far as philosophical theories of confirmation are con...

There is an ongoing methodological debate in philosophy of science concerning the use of case studies as evidence for and/or against theories about science. In this paper, I aim to make a contribution to this debate by taking an empirical approach. I present the results of a systematic survey of the PhilSci-Archive, which suggest that a sizeable proportion of papers in philosophy of science contain appeals to case studies, as indicated by the occurrence of the indicator words “case study” and/or (...) “case studies.” These results are confirmed by data mined from the JSTOR database on research articles published in leading journals in the field: Philosophy of Science, the British Journal for the Philosophy of Science (BJPS), and the Journal for General Philosophy of Science (JGPS), as well as the Proceedings of the Biennial Meeting of the Philosophy of Science Association (PSA). The data also show upward trends in appeals to case studies in articles published in Philosophy of Science, the BJPS, and the JGPS. The empirical work I have done for this paper provides philosophers of science who are wary of the use of case studies as evidence for and/or against theories about science with a way to do philosophy of science that is informed by data rather than case studies. (shrink)

More than 50 years after the publication of Thomas Kuhn’s seminal book, The Structure of Scientific Revolutions, this volume assesses the adequacy of the Kuhnian model in explaining certain aspects of science, particularly the social and epistemic aspects of science. One argument put forward is that there are no good reasons to accept Kuhn’s incommensurability thesis, according to which scientific revolutions involve the replacement of theories with conceptually incompatible ones. Perhaps, therefore, it is time for another “decisive transformation in the (...) image of science by which we are now possessed.” Only this time, the image of science that needs to be transformed is the Kuhnian one. Does the Kuhnian image of science provide an adequate model of scientific practice? If we abandon the Kuhnian picture of revolutionary change and incommensurability, what consequences would follow from that vis-à-vis our understanding of scientific knowledge as a social endeavour? -/- The essays in this collection continue this debate, offering a critical examination of the arguments for and against the Kuhnian image of science as well as their implications for our understanding of science as a social and epistemic enterprise. (shrink)

In his latest attack, even though he claims to be a practitioner of “close reading” (Wills 2018b, 34), it appears that Wills still has not bothered to read the paper in which I defend the thesis he seeks to attack (Mizrahi 2017a), or any of the papers in my exchange with Brown (Mizrahi 2017b; 2018a), as evidenced by the fact that he does not cite them at all. This explains why Wills completely misunderstands Weak Scientism and the arguments for the (...) quantitative superiority (in terms of research output and research impact) as well as qualitative superiority (in terms of explanatory, predictive, and instrumental success) of scientific knowledge over non-scientific knowledge. (shrink)

In my (2017a), I defend a view I call Weak Scientism, which is the view that knowledge produced by scientific disciplines is better than knowledge produced by non-scientific disciplines. Scientific knowledge can be said to be quantitatively better than non-scientific knowledge insofar as scientific disciplines produce more impactful knowledge–in the form of scholarly publications–than non-scientific disciplines (as measured by research output and research impact). Scientific knowledge can be said to be qualitatively better than non-scientific knowledge insofar as such knowledge is (...) explanatorily, instrumentally, and predictively more successful than non-scientific knowledge. Brown (2017a) raises several objections against my defense of Weak Scientism and I have replied to his objections (Mizrahi 2017b), thereby showing again that Weak Scientism is a defensible view. Since then, Brown (2017b) has reiterated his objections in another reply on SERRC. In this paper, I respond to Brown's objections, thereby showing once more that Weak Scientism is a defensible view. (shrink)

In this paper, I argue that, if ‘the overrepresentation of Christian theists in analytic philosophy of religion is unhealthy for the field, since they would be too much influenced by prior beliefs when evaluating religious arguments’ (De Cruz and De Smedt (2016), 119), then a first step toward a potential remedy is this: analytic philosophers of religion need to restructure their analytical tasks. For one way to mitigate the effects of confirmation bias, which may be influencing how analytic philosophers of (...) religion evaluate arguments in Analytical Philosophy of Religion (APR), is to consider other points of view. Applied to APR, this means considering religious beliefs, questions, and arguments couched in non-Christian terms. In this paper, I focus on Islam in particular. My aim is to show that Islam is a fertile ground of philosophical questions and arguments for analytic philosophers of religion to engage with. Engaging with questions and arguments couched in non-Christian terms would help make work in APR more diverse and inclusive of religions other than Christianity, which in turn would also be a first step toward attracting non-Christians to APR. (shrink)

ABSTRACTThis discussion note aims to contribute to the ongoing debate over the nature of scientific progress. I argue against the semantic view of scientific progress, according to which scientific progress consists in approximation to truth or increasing verisimilitude. If the semantic view of scientific progress were correct, then scientists would make scientific progress simply by arbitrarily adding true disjuncts to their hypotheses or theories. Given that it is not the case that scientists could make scientific progress simply by arbitrarily adding (...) true disjuncts to their hypotheses or theories, it follows that the semantic view of scientific progress is incorrect. (shrink)

Bernard Wills (2018) joins Christopher Brown (2017, 2018) in criticizing my defense of Weak Scientism (Mizrahi 2017a, 2017b, 2018a). Unfortunately, it seems that Wills did not read my latest defense of Weak Scientism carefully, nor does he cite any of the other papers in my exchange with Brown.

In this paper, I argue that the “positive argument” for Constructive Empiricism (CE), according to which CE “makes better sense of science, and of scientific activity, than realism does” (van Fraassen 1980, 73), is an Inference to the Best Explanation (IBE). But constructive empiricists are critical of IBE, and thus they have to be critical of their own “positive argument” for CE. If my argument is sound, then constructive empiricists are in the awkward position of having to reject their own (...) “positive argument” for CE by their own lights. (shrink)

In this paper, I respond to Philip Atkins’ reply to my attempt to explain why Gettier cases (and Gettier-style cases) are misleading. I have argued that Gettier cases (and Gettier-style cases) are misdealing because the candidates for knowledge in such cases contain ambiguous designators. Atkins denies that Gettier’s original cases contain ambiguous designators and offers his intuition that the subjects in Gettier’s original cases do not know. I argue that his reply amounts to mere intuition mongering and I explain why (...) Gettier cases, even Atkins’ revised version of Gettier’s Case I, still contain ambiguous designators. (shrink)

In this paper, I propose that applying the methods of data science to “the problem of whether mathematical explanations occur within mathematics itself” (Mancosu 2018) might be a fruitful way to shed new light on the problem. By carefully selecting indicator words for explanation and justification, and then systematically searching for these indicators in databases of scholarly works in mathematics, we can get an idea of how mathematicians use these terms in mathematical practice and with what frequency. The results of (...) this empirical study suggest that mathematical explanations do occur in research articles published in mathematics journals, as indicated by the occurrence of explanation indicators. When compared with the use of justification indicators, however, the data suggest that justifications occur much more frequently than explanations in scholarly mathematical practice. The results also suggest that justificatory proofs occur much more frequently than explanatory proofs, thus suggesting that proof may be playing a larger justificatory role than an explanatory role in scholarly mathematical practice. (shrink)

In their reviews of The Kuhnian Image of Science: Time for a Decisive Transformation? (2018), both Markus Arnold (2018) and Amanda Bryant (2018) complain that the contributors who criticize Kuhn’s theory of scientific change have misconstrued his philosophy of science and they praise those who seek to defend the Kuhnian image of science. In what follows, then, I would like to address their claims about misconstruing Kuhn’s theory of scientific change. But my focus here, as in the book, will be (...) the evidence (or lack thereof) for the Kuhnian image of science. I will begin with Arnold’s review and then move on to Bryant’s review. (shrink)

When the phrase “playing God” is used in debates concerning the use of new technologies, such as cloning or genetic engineering, it is usually interpreted as a warning not to interfere with God’s creation or nature. I think that this interpretation of “playing God” arguments as a call to non-interference with nature is too narrow. In this paper, I propose an alternative interpretation of “playing God” arguments. Taking an argumentation theory approach, I provide an argumentation scheme and accompanying critical questions (...) that capture the moral concerns expressed by “playing God” arguments. If I am right, then “playing God” arguments should be understood, not as a warning to leave God’s creation or nature alone, but rather as an invitation to think carefully about all the ways in which the use of new technologies could go seriously wrong. (shrink)

It is often said that ‘every logical truth is obvious’ (Quine 1970: 82), that the ‘axioms and rules of logic are true in an obvious way’ (Murawski 2014: 87), or that ‘logic is a theory of the obvious’ (Sher 1999: 207). In this chapter, I set out to test empirically how the idea that logic is obvious is reflected in the scholarly work of logicians and philosophers of logic. My approach is data-driven. That is to say, I propose that systematically (...) searching for patterns of usage in databases of scholarly works, such as JSTOR, can provide new insights into the ways in which the idea that logic is obvious is reflected in logical and philosophical practice, i.e., in the arguments that logicians and philosophers of logic actually make in their published work. (shrink)

This paper defends the view, put roughly, that to think that p is to guess that p is the answer to the question at hand, and that to think that p rationally is for one’s guess to that question to be in a certain sense non-arbitrary. Some theses that will be argued for along the way include: that thinking is question-sensitive and, correspondingly, that ‘thinks’ is context-sensitive; that it can be rational to think that p while having arbitrarily low credence (...) that p; that, nonetheless, rational thinking is closed under entailment; that thinking does not supervene on credence; and that in many cases what one thinks on certain matters is, in a very literal sense, a choice. Finally, since there are strong reasons to believe that thinking just is believing, there are strong reasons to think that all this goes for belief as well. (shrink)

In this paper, I present the results of an experimental study on intuitions about moral obligation (ought) and ability (can). Many philosophers accept as an axiom the principle known as “Ought Implies Can” (OIC). If the truth of OIC is intuitive, such that it is accepted by many philosophers as an axiom, then we would expect people to judge that agents who are unable to perform an action are not morally obligated to perform that action. The results of my experimental (...) study show that participants were more inclined to judge that an agent ought to perform an action than that the agent can perform the action. Overall, participants said that an agent ought to perform an action even when they said that the agent cannot do it. I discuss the implications of these results for the debate over OIC. (shrink)

Experimental philosophers have challenged friends of the expertise defense to show that the intuitive judgments of professional philosophers are different from the intuitive judgments of nonphilosophers, and the intuitive judgments of professional philosophers are better than the intuitive judgments of nonphilosophers, in ways that are relevant to the truth or falsity of such judgments. Friends of the expertise defense have responded by arguing that the burden of proof lies with experimental philosophers. This article sketches three arguments which show that both (...) and are probably false. If its arguments are cogent, then shifting the burden of proof is a futile move, since philosophical training makes no difference so far as making intuitive judgments in response to hypothetical cases is concerned. (shrink)

Philosophy is often divided into two traditions: analytic and continental philosophy. Characterizing the analytic-continental divide, however, is no easy task. Some philosophers explain the divide in terms of the place of argument in these traditions. This raises the following questions: Is analytic philosophy rife with arguments while continental philosophy is devoid of arguments? Or can different types of arguments be found in analytic and continental philosophy? This paper presents the results of an empirical study of a large corpus of philosophical (...) texts mined from the JSTOR database (n = 53,260) designed to find patterns of argumentation by type. Overall, the results suggest that there are no significant differences between the types of arguments advanced in analytic and continental philosophy journal articles. The findings, therefore, provide no empirical support to the hypothesis that the divide between analytic and continental philosophy has to do with the place of argument in these traditions. (shrink)

I have argued that Gettier cases are misleading because, even though they appear to be cases of knowledge failure, they are in fact cases of semantic failure. Atkins has responded to my original paper and I have replied to his response. He has then responded again to insist that he has the so-called “Gettier intuition.” But he now admits that intuitions are only defeasible, not conclusive, evidence for and/or against philosophical theories. I address the implications of Atkins’ admission in this (...) paper and I again show that his attempts to revise Gettier’s original cases such that they do not involve semantic failures are unsuccessful. (shrink)

In this discussion note, I put forth an argument from the factivity of knowledge for the conclusion that knowledge is epistemic certainty. If this argument is sound, then epistemologists who think that knowledge is factive are thereby also committed to the view that knowledge is epistemic certainty.

In this article, I argue that arguments from the history of science against scientific realism, like the arguments advanced by P. Kyle Stanford and Peter Vickers, are fallacious. The so-called Old Induction, like Vickers's, and New Induction, like Stanford's, are both guilty of confirmation bias—specifically, of cherry-picking evidence that allegedly challenges scientific realism while ignoring evidence to the contrary. I also show that the historical episodes that Stanford adduces in support of his New Induction are indeterminate between a pessimistic and (...) an optimistic interpretation. For these reasons, these arguments are fallacious, and thus do not pose a serious challenge to scientific realism. (shrink)

In a paper and a reply to critics published in _Informal Logic_, I argue that arguments from expert opinion are weak arguments. To appeal to expert opinion is to take an expert’s judgment that _p_ is the case as evidence for _p_. Such appeals to expert opinion are weak, I argue, because the fact that an expert judges that _p_ does not make it significantly more likely that _p_ is true or probable, as evidence from empirical studies on expert performance (...) suggests. Unlike other critics of this argument, who take issue with the empirical evidence on expert performance, David Botting says that he wants to take issue with the premise that reliability is a necessary condition for the strength of appeals to expert opinion. I respond to Botting’s objections and argue that they miss their intended target. I also argue that his attempt to show that arguments from expert opinion are strong is unsuccessful. (shrink)

Alexander Bird argues for an epistemic account of scientific progress, whereas Darrell Rowbottom argues for a semantic account. Both appeal to intuitions about hypothetical cases in support of their accounts. Since the methodological significance of such appeals to intuition is unclear, I think that a new approach might be fruitful at this stage in the debate. So I propose to abandon appeals to intuition and look at scientific practice instead. I discuss two cases that illustrate the way in which scientists (...) make judgments about progress. As far as scientists are concerned, progress is made when scientific discoveries contribute to the increase of scientific knowledge of the following sorts: empirical, theoretical, practical, and methodological. I then propose to articulate an account of progress that does justice to this broad conception of progress employed by scientists. I discuss one way of doing so, namely, by expanding our notion of scientific knowledge to include both know-that and know-how. (shrink)

In their attempt to defend philosophy from accusations of uselessness made by prominent scientists, such as Stephen Hawking, some philosophers respond with the charge of ‘scientism.’ This charge makes endorsing a scientistic stance, a mistake by definition. For this reason, it begs the question against these critics of philosophy, or anyone who is inclined to endorse a scientistic stance, and turns the scientism debate into a verbal dispute. In this paper, I propose a different definition of scientism, and thus a (...) new way of looking at the scientism debate. Those philosophers who seek to defend philosophy against accusations of uselessness would do philosophy a much better service, I submit, if they were to engage with the definition of scientism put forth in this paper, rather than simply make it analytic that scientism is a mistake. (shrink)

In this article, through a critical examination of K. Brad Wray's version of the argument from underconsideration against scientific realism, I articulate a modest version of scientific realism. This modest realist position, which I call ‘relative realism’, preserves the scientific realist's optimism about science's ability to get closer to the truth while, at the same time, taking on board the antirealist's premise that theory evaluation is comparative, and thus that there are no good reasons to think that science's best theories (...) are close to the truth. (shrink)

This is a reply to Howard Sankey’s comment (“Factivity or Grounds? Comment on Mizrahi”) on my paper, “You Can’t Handle the Truth: Knowledge = Epistemic Certainty,” in which I present an argument from the factivity of knowledge for the conclusion that knowledge is epistemic certainty. While Sankey is right that factivity does not entail epistemic certainty, the factivity of knowledge does entail that knowledge is epistemic certainty.

In this paper, I argue that the method of cases (namely, the method of using intuitive judgments elicited by intuition pumps as evidence for and/or against philosophical theories) is not a reliable method of generating evidence for and/or against philosophical theories. In other words, the method of cases is unlikely to generate accurate judgments more often than not. This is so because, if perception and intuition are analogous in epistemically relevant respects, then using intuition pumps to elicit intuitive judgments is (...) like using illusions to elicit perceptual judgments. In both cases, judgments are made under bad epistemic circumstances. (shrink)

The aim of this paper is to contribute to the debate over the nature of scientific progress in philosophy of science by taking a quantitative, corpus-based approach. By employing the methods of data science and corpus linguistics, the following philosophical accounts of scientific progress are tested empirically: the semantic account of scientific progress, the epistemic account of scientific progress, and the noetic account of scientific progress. Overall, the results of this quantitative, corpus-based study lend some empirical support to the epistemic (...) and the noetic accounts over the semantic account of scientific progress, for they suggest that practicing scientists use the terms ‘knowledge’ and ‘understanding’ significantly more often than the term ‘truth’ when they talk about the aims or goals of scientific research in their published works. But the results do not favor the epistemic account over the noetic account, or vice versa, for they reveal no significant differences between the frequency with which practicing scientists use the terms ‘knowledge’ and ‘understanding’ when they talk about the aims or goals of scientific research in their published works. (shrink)

The attempt to define meaning arouses numerous questions, such as whether life can be meaningful without actions devoted to a central purpose or whether the latter guarantee a meaningful life. Communities of inquiry are relevant in this context because they create relationships within and between people and the environment. The more they address relations—social, cognitive, emotional, etc.—that tie-in with the children’s world even if not in a concrete fashion, the more they enable young people to search for and find meaning. (...) Examining the way in which philosophical communities of inquiry serve as a dialogical space that enables a search for meaning on the personal and collective plane, this article seeks to expand the discussion of how/whether finding meaning on a private or communal level can promote recognition of the existential uniqueness of each individual and the development of a sense of responsibility for him or her. Grounded in the writings of Matthew Lipman, it links his ideas about finding meaning in philosophical communities of inquiry with those of Jean-Paul Sartre, Viktor Frankl, and Emmanuel Levinas, in particular with regard to the association between meaning and responsibility. (shrink)

In this paper, I propose that, in addition to the multiverse hypothesis, which is commonly taken to be an alternative explanation for fine-tuning, other than the design hypothesis, the simulation hypothesis is another explanation for fine-tuning. I then argue that the simulation hypothesis undercuts the alleged evidential connection between ‘designer’ and ‘supernatural designer of immense power and knowledge’ in much the same way that the multiverse hypothesis undercuts the alleged evidential connection between ‘fine-tuning’ and ‘fine-tuner’ (or ‘designer’). If this is (...) correct, then the fine-tuning argument is a weak argument for the existence of God. (shrink)

In True enough,, Elgin argues against veritism, which is the view that truth is the paramount epistemic objective. Elgin’s argument against veritism proceeds from considering the role that models, idealizations, and thought experiments play in science to the conclusion that veritism is unacceptable. In this commentary, I argue that Elgin’s argument fails as an argument against veritism. I sketch a refutation by logical analogy of Elgin’s argument. Just as one can aim at gold medals and still find approximations to gold, (...) such as silver and bronze medals, to be acceptable and honest achievements in competitive sports, one can aim at full truths as the paramount epistemic objective and still find approximations to truth, such as models and idealizations, to be acceptable and honest achievements in scientific inquiry. (shrink)

In this paper, I sketch an answer to the question “Why be an intellectually humble philosopher?” I argue that, as far as philosophical argumentation is concerned, the historical record of Western Philosophy provides a straightforward answer to this question. That is, the historical record of philosophical argumentation, which is a track record that is marked by an abundance of alternative theories and serious problems for those theories, can teach us important lessons about the limits of philosophical argumentation. These lessons, in (...) turn, show why philosophers should argue with humility. (shrink)

In this paper, I respond to Sterpetti’s attempt to defend Kyle P. Stanford’s Problem of Unconceived Alternatives and his New Induction over the History of Science from my reductio argument outlined in Mizrahi :59–68, 2016a). I discuss what I take to be the ways in which Sterpetti has misconstrued my argument against Stanford’s NIS, in particular, that it is a reductio, not a dilemma, as Sterpetti erroneously thinks. I argue that antirealists who endorse Stanford’s NIS still face an absurd consequence (...) of this argument, namely, that they should not believe their own brand of scientific antirealism. (shrink)

In this paper, I argue that appeals to intuition are strong arguments just in case there is an agreement among the relevant philosophers concerning the intuition in question. Otherwise, appeals to intuition are weak arguments.

In this article, I present a schema for generating counterexamples to the argument form known as Hypothetical Syllogism with indicative conditionals. If my schema for generating counterexamples to HS works as I think it does, then HS is invalid for indicative conditionals.

According to the Ought-Implies-Can principle (OIC), an agent ought to perform a certain action only if the agent can perform that action. Proponents of OIC interpret this supposed implication in several ways. Some argue that the implication in question is a logical one, namely, entailment. Some think that the relation between ‘ought’ and ‘can’ is a relation of presupposition. Still others argue that ‘ought’ conversationally implicates ‘can’. Opponents of OIC offer a variety of counterexamples in an attempt to show that (...) there are cases in which an agent ought to perform a certain action even though she cannot perform that action. Such counterexamples often involve either culpable or nonculpable inability. In cases of culpable inability, the agent renders herself unable to fulfill an obligation. For example, a student is unable to submit a paper on the due date because she procrastinated until it became too late to write a paper by the assigned deadline. In cases of non-culpable inability, the agent somehow becomes unable to fulfill an obligation, through no fault of her own. For example, an agent becomes unable to pay back a loan to a bank because she was robbed on her way to the bank. This paper attempts to offer counterexamples to OIC of a sort different from the one discussed by opponents of OIC so far. If these counterexamples are correct, then they seem to suggest that there are cases in which an agent has an obligation to perform an action even though she may not be able to perform that action, and thus OIC is false. In other words, ‘ought’ does not imply ‘can’. (shrink)

In this paper, I discuss an argument for the existence of God known as “The Argument from the Survival of the Jews.” This argument has the form of an Inference to the Best Explanation (IBE). It proceeds from the phenomenon of Jewish survival to the existence of God as the best explanation for this phenomenon. I will argue that, even if we grant that Jewish survival is a remarkable occurrence that demands an explanation, and even if we gloss over the (...) difficulties in defining the terms “Jewish” and “survive,” the argument ultimately fails as an argument for the existence of God. It fails because it postulates divine supervision in order to explain Jewish endurance, but it doesn’t provide any clues as to what might be the underlying mechanism at work. (shrink)

In “What’s So Bad about Scientism?” (Mizrahi 2017), I argue that Weak Scientism, the view that “Of all the knowledge we have, scientific knowledge is the best knowledge” (Mizrahi 2017, 354; emphasis in original) is a defensible position. That is to say, Weak Scientism “can be successfully defended against objections” (Mizrahi 2017, 354). In his response to Mizrahi (2017), Christopher Brown (2017) provides more objections against Weak Scientism, and thus another opportunity for me to show that Weak Scientism is a (...) defensible position, which is what I will do in this reply. In fact, I think that I have already addressed Brown’s (2017) objections in Mizrahi (2017), so I will simply highlight these arguments here. (shrink)

I report the results of a follow-up study, designed to address concerns raised by Kurthy and Lawford-Smith in response to my original study on intuitions about moral obligation (ought) and ability (can). Like the results of the original study, the results of the follow-up study do not support the hypothesis that OIC is intuitive. The results of both studies suggest that OIC is probably not a principle of ordinary moral cognition. As I have argued in my paper, I take this (...) to mean that OIC can no longer be taken as axiomatic. It must be argued for without appealing to intuitions. (shrink)

In this paper, I argue that the “Ought Implies Can” (OIC) principle, as it is employed in epistemology, particularly in the literature on epistemic norms, is open to counterexamples. I present a counterexample to OIC and discuss several objections to it. If this counterexample works, then it shows that it is possible that S ought to believe that p, even though S cannot believe that p. If this is correct, then OIC, considered from an epistemic point of view, is false, (...) since it is supposed to hold for any S and any p. (shrink)

In this paper, I argue that appeals to intuition are weak arguments because intellectual intuition is an unreliable belief-forming process, since it yields incompatible verdicts in response to the same cases, and since the inference from 'It seems to S that p' to 'p' is unreliable. Since the reliability of intellectual intuition is a necessary condition for strong appeals to intuition, it follows that appeals to intuition are weak arguments.

In this paper, I argue that, as far as Gettier cases are concerned, appearances are deceiving. That is, Gettier cases merely appear to be cases of epistemic failure (i.e., failing to know that p) but are in fact cases of semantic failure (i.e., failing to refer to x). Gettier cases are cases of reference failure because the candidates for knowledge in these cases contain ambiguous designators. If this is correct, then we may simply be mistaking semantic facts for epistemic facts (...) when we consider Gettier cases. This, in turn, is a good reason not to assign much, if any, evidential weight to Gettier intuitions (i.e., that S doesn’t know that p in a Gettier case). (shrink)

In this paper, I argue that, just as the problem of unconceived alternatives provides a basis for a New Induction on the History of Science to the effect that a realist view of science is unwarranted, the problem of unconceived objections provides a basis for a New Induction on the History of Philosophy to the effect that a realist view of philosophy is unwarranted. I raise this problem not only for skepticism’s sake but also for the sake of making a (...) point about philosophical argumentation, namely, that anticipating objections to one’s claim is not the same as supporting one’s claim. In other words, defending p from objections does not amount to support or evidence for p. This, in turn, presents dialectical and pragma-dialectical approaches to argumentation with the following question: does proper argumentation require that arguers anticipate and respond to unconceived objections? (shrink)