The counterfactual account of physical computation is simple and, for the most part, very attractive. However, it is usually thought to trivialize the notion of physical computation insofar as it implies ‘limited pancomputationalism’, this being the doctrine that every deterministic physical system computes some function. Should we bite the bullet and accept limited pancomputationalism, or reject the counterfactual account as untenable? Jack Copeland would have us do neither of the above. He attempts to thread a path between the (...) two horns of the dilemma by buttressing the counterfactual account with extra conditions intended to block certain classes of deterministic physical systems from qualifying as physical computers. His theory is called the ‘algorithm execution account’. Here we show that the algorithm execution account entails limited pancomputationalism, despite Copeland’s argument to the contrary. We suggest, partly on this basis, that the counterfactual account should be accepted as it stands, pancomputationalist warts and all. (shrink)

The suite of secretive national security programs initiated in the US since 9/11 has created debate not only about the merits of targeted killing, torture, secret detention, cyberwar, global signals intercepts, and data-mining, but about the very secrecy in which these programs were conceived, debated by government officials, and implemented. Law must be revealed to those who are expected to comply with its demands. Law is a mere pretext for coercion if the laws permitting the government to coerce people for (...) non-compliance are concealed. The purpose of this essay is to determine whether inhabitants of a liberal state—a type of state tracing the legitimacy of its coercive actions to the consent of the governed—also need to know the internal protocols and legal findings of the government agencies ostensibly serving them. To put this question another way, what, if anything, may government agencies in liberal states keep secret? (shrink)

Inspired by recent breakthroughs in predictive modeling, practitioners in both industry and government have turned to machine learning with hopes of operationalizing predictions to drive automated decisions. Unfortunately, many social desiderata concerning consequential decisions, such as justice or fairness, have no natural formulation within a purely predictive framework. In efforts to mitigate these problems, researchers have proposed a variety of metrics for quantifying deviations from various statistical parities that we might expect to observe in a fair world and offered a (...) variety of algorithms in attempts to satisfy subsets of these parities or to trade o the degree to which they are satised against utility. In this paper, we connect this approach to fair machine learning to the literature on ideal and non-ideal methodological approaches in political philosophy. The ideal approach requires positing the principles according to which a just world would operate. In the most straightforward application of ideal theory, one supports a proposed policy by arguing that it closes a discrepancy between the real and the perfectly just world. However, by failing to account for the mechanisms by which our non-ideal world arose, the responsibilities of various decision-makers, and the impacts of proposed policies, naive applications of ideal thinking can lead to misguided interventions. In this paper, we demonstrate a connection between the fair machine learning literature and the ideal approach in political philosophy, and argue that the increasingly apparent shortcomings of proposed fair machine learning algorithms reflect broader troubles faced by the ideal approach. We conclude with a critical discussion of the harms of misguided solutions, a reinterpretation of impossibility results, and directions for future research. (shrink)

Algorithms can now identify patterns and correlations in the (big) datasets, and predict outcomes based on those identified patterns and correlations with the use of machine learning techniques and big data, decisions can then be made by algorithms themselves in accordance with the predicted outcomes. Yet, algorithms can inherit questionable values from the datasets and acquire biases in the course of (machine) learning, and automated algorithmic decision-making makes it more difficult for people to see algorithms as biased. While researchers have (...) taken the problem of algorithmic bias seriously, but the current discussion on algorithmic fairness tends to conceptualize ‘fairness’ in algorithmic fairness primarily as a technical issue and attempts to implement pre-existing ideas of ‘fairness’ into algorithms. In this paper, I show that such a view of algorithmic fairness as technical issue is unsatisfactory for the type of problem algorithmic fairness presents. Since decisions on fairness measure and the related techniques for algorithms essentially involve choices between competing values, ‘fairness’ in algorithmic fairness should be conceptualized first and foremost as a political issue, and it should be (re)solved by democratic communication. The aim of this paper, therefore, is to explicitly reconceptualize algorithmic fairness as a political question and suggest the current discussion of algorithmic fairness can be strengthened by adopting the accountability for reasonableness framework. (shrink)

Since the Enlightenment, there have been advocates for the rationalizing efficiency of enlightened sovereigns, bureaucrats, and technocrats. Today these enthusiasms are joined by calls for replacing or augmenting government with algorithms and artificial intelligence, a process already substantially under way. Bureaucracies are in effect algorithms created by technocrats that systematize governance, and their automation simply removes bureaucrats and paper. The growth of algorithmic governance can already be seen in the automation of social services, regulatory oversight, policing, the justice system, and (...) the military. However, there have also always been justified democratic and economic criticisms of autocracy, bureaucracy, technocracy, and algorithmic governance. Bureaucrats, technocrats, and algorithms embody biases that tend to serve the interests of elites, and all require transparency and democratic accountability, oversight individual citizens are ill equipped to exercise. As state apparatuses are increasingly automated, mechanisms for collective action and democratic oversight also need to be automated. Algorithms and cyborg citizenry will enable a posthuman democracy. Democratically accountable algorithmic governance, enabled by artificial intelligence and human enhancement, can automate bottom-up citizen surveillance, inform debate, aggregate decision making, and ensure the efficient working of the gradually withering state. As paid work disappears and we transition to a postcapitalist economy with a universal basic income, market mechanisms can be replaced with democratic planning. Indeed, only algorithmic governance can secure our future against accelerating threats from technological innovation. (shrink)

Over the past decade, scholars, institutions, and activists have voiced strong concerns about the potential of automated decision systems to indirectly discriminate against vulnerable groups. This article analyses the ethics of algorithmic indirect discrimination, and argues that we can explain what is morally bad about such discrimination by reference to the fact that it causes harm. The article first sketches certain elements of the technical and conceptual background, including definitions of direct and indirect algorithmic differential treatment. It next introduces three (...) prominent accounts of fairness as potential explanations if the badness of algorithmic indirect discrimination, but argues that all three are vulnerable to powerful levelling-down-style objections. Instead, the article demonstrates how proper attention to the way differences in decision-scenarios affect the distribution of harms can help us account for intuitions in prominent cases. Finally, the article considers a potential objection based on the fact that certain forms of algorithmic indirect discrimination appear to distribute rather than cause harm, and notes that we can explain how such distributions cause harm by attending to differences in individual and group vulnerability. (shrink)

For more than two decades, police in the United States have used facial recognition to surveil civilians. Local police departments deploy facial recognition technology to identify protestors’ faces while federal law enforcement agencies quietly amass driver’s license and social media photos to build databases containing billions of faces. Yet, despite the widespread use of facial recognition in law enforcement, there are neither federal laws governing the deployment of this technology nor regulations settings standards with respect to its development. To make (...) matters worse, the Fourth Amendment—intended to limit police power and enacted to protect against unreasonable searches—has struggled to rein in new surveillance technologies since its inception. -/- This Article examines the Supreme Court’s Fourth Amendment jurisprudence leading up to Carpenter v. United States and suggests that the Court is reinterpreting the amendment for the digital age. Still, the too-slow expansion of privacy protections raises challenging questions about racial bias, the legitimacy of police power, and ethical issues in artificial intelligence design. This Article proposes the development of an algorithmic auditing and accountability market that not only sets standards for AI development and limitations on governmental use of facial recognition but encourages collaboration between public interest technologists and regulators. Beyond the necessary changes to the technological and legal landscape, the current system of policing must also be reevaluated if hard-won civil liberties are to endure. (shrink)

The application of machine-learning technologies to medical practice promises to enhance the capabilities of healthcare professionals in the assessment, diagnosis, and treatment, of medical conditions. However, there is growing concern that algorithmic bias may perpetuate or exacerbate existing health inequalities. Hence, it matters that we make precise the different respects in which algorithmic bias can arise in medicine, and also make clear the normative relevance of these different kinds of algorithmic bias for broader questions about justice and fairness in healthcare. (...) In this paper, we provide the building blocks for an account of algorithmic bias and its normative relevance in medicine. (shrink)

The prospective introduction of autonomous cars into public traffic raises the question of how such systems should behave when an accident is inevitable. Due to concerns with self-interest and liberal legitimacy that have become paramount in the emerging debate, a contractarian framework seems to provide a particularly attractive means of approaching this problem. We examine one such attempt, which derives a harm minimisation rule from the assumptions of rational self-interest and ignorance of one’s position in a future accident. We contend, (...) however, that both contractarian approaches and harm minimisation standards are flawed, due to a failure to account for the fundamental difference between those ‘involved’ and ‘uninvolved’ in an impending crash. Drawing from classical works on the trolley problem, we show how this notion can be substantiated by reference to either the distinction between negative and positive rights, or to differences in people’s claims. By supplementing harm minimisation with corresponding constraints, we can develop crash algorithms for autonomous cars which are both ethically adequate and promise to overcome certain significant practical barriers to implementation. (shrink)

Philosophers have established that certain ethically important val- ues are modally robust in the sense that they systematically deliver correlative benefits across a range of counterfactual scenarios. In this paper, we contend that recourse – the systematic process of reversing unfavorable decisions by algorithms and bureaucracies across a range of counterfactual scenarios – is such a modally ro- bust good. In particular, we argue that two essential components of a good life – temporally extended agency and trust – are under- (...) written by recourse. We critique existing approaches to the conceptualization, op- erationalization and implementation of recourse. Based on these criticisms, we suggest a revised approach to recourse and give ex- amples of how it might be implemented – especially for those who are least well off. (shrink)

In philosophy of mind, zombies are imaginary creatures that are exact physical duplicates of conscious subjects but for whom there is no first-personal experience. Zombies are meant to show that physicalism—the theory that the universe is made up entirely out of physical components—is false. In this paper, I apply the zombie thought experiment to the realm of morality to assess whether moral agency is something independent from sentience. Algorithms, I argue, are a kind of functional moral zombie, such that thinking (...) about the latter can help us better understand and regulate the former. I contend that the main reason why algorithms can be neither autonomous nor accountable is that they lack sentience. Moral zombies and algorithms are incoherent as moral agents because they lack the necessary moral understanding to be morally responsible. To understand what it means to inflict pain on someone, it is necessary to have experiential knowledge of pain. At most, for an algorithm that feels nothing, ‘values’ will be items on a list, possibly prioritised in a certain way according to a number that represents weightiness. But entities that do not feel cannot value, and beings that do not value cannot act for moral reasons. (shrink)

We consider two ways one might use algorithmic randomness to characterize a probabilistic law. The first is a generative chance* law. Such laws involve a nonstandard notion of chance. The second is a probabilistic* constraining law. Such laws impose relative frequency and randomness constraints that every physically possible world must satisfy. While each notion has virtues, we argue that the latter has advantages over the former. It supports a unified governing account of non-Humean laws and provides independently motivated solutions (...) to issues in the Humean best-system account. On both notions, we have a much tighter connection between probabilistic laws and their corresponding sets of possible worlds. Certain histories permitted by traditional probabilistic laws are ruled out as physically impossible. As a result, such laws avoid one variety of empirical underdetermination, but the approach reveals other varieties of underdetermination that are typically overlooked. (shrink)

A common criticism of the use of algorithms in criminal justice is that algorithms and their determinations are in some sense ‘opaque’—that is, difficult or impossible to understand, whether because of their complexity or because of intellectual property protections. Scholars have noted some key problems with opacity, including that opacity can mask unfair treatment and threaten public accountability. In this paper, we explore a different but related concern with algorithmic opacity, which centers on the role of public trust in grounding (...) the legitimacy of criminal justice institutions. We argue that algorithmic opacity threatens the trustworthiness of criminal justice institutions, which in turn threatens their legitimacy. We first offer an account of institutional trustworthiness before showing how opacity threatens to undermine an institution’s trustworthiness. We then explore how threats to trustworthiness affect institutional legitimacy. Finally, we offer some policy recommendations to mitigate the threat to trustworthiness posed by the opacity problem. (shrink)

Existing discussions about automated decision-making focus primarily on its inputs and outputs, raising questions about data collection and privacy on one hand and accuracy and fairness on the other. Less attention has been devoted to critically examining the temporality of decision-making processes—the speed at which automated decisions are reached. In this paper, I identify four dimensions of algorithmic speed that merit closer analysis. Duration (how much time it takes to reach a judgment), timing (when automated systems intervene in the activity (...) being evaluated), frequency (how often evaluations are performed), and lived time (the human experience of algorithmic speed) are interrelated, but distinct, features of automated decision-making. Choices about the temporal structure of automated decision-making systems have normative implications, which I describe in terms of "disruption," "displacement," "re-calibration," and "temporal fairness," with values such as accuracy, fairness, accountability, and legitimacy hanging in the balance. As computational tools are increasingly tasked with making judgments about human activities and practices, the designers of decision-making systems will have to reckon, I argue, with when—and how fast—judgments ought to be rendered. Though computers are capable of reaching decisions at incredible speeds, failing to account for the temporality of automated decision-making risks misapprehending the costs and benefits automation promises. (shrink)

Abstract—Breast cancer is considered the second most common cancer in women compared to all other cancers. It is fatal in less than half of all cases and is the main cause of mortality in women. It accounts for 16% of all cancer mortalities worldwide. Early diagnosis of breast cancer increases the chance of recovery. Data mining techniques can be utilized in the early diagnosis of breast cancer. In this paper, an academic experimental breast cancer dataset is used to perform a (...) data mining practical experiment using the Waikato Environment for Knowledge Analysis (WEKA) tool. The WEKA Java application represents a rich resource for conducting performance metrics during the execution of experiments. Pre-processing and feature extraction are used to optimize the data. The classification process used in this study was summarized through thirteen experiments. Additionally, 10 experiments using various different classification algorithms were conducted. The introduced algorithms were: Naïve Bayes, Logistic Regression, Lazy IBK (Instance-Bases learning with parameter K), Lazy Kstar, Lazy Locally Weighted Learner, Rules ZeroR, Decision Stump, Decision Trees J48, Random Forest and Random Trees. The process of producing a predictive model was automated with the use of classification accuracy. Further, several experiments on classification of Wisconsin Diagnostic Breast Cancer and Wisconsin Breast Cancer, were conducted to compare the success rates of the different methods. Results conclude that Lazy IBK classifier k-NN can achieve 98% accuracy among other classifiers. The main advantages of the study were the compactness of using 13 different data mining models and 10 different performance measurements, and plotting figures of classifications errors. (shrink)

Big Data must be processed with advanced collection and analysis tools, based on predetermined algorithms, in order to obtain relevant information. Algorithms must also take into account invisible aspects for direct perceptions. Big Data issues is multi-layered. A distributed parallel architecture distributes data on multiple servers (parallel execution environments) thus dramatically improving data processing speeds. Big Data provides an infrastructure that allows for highlighting uncertainties, performance, and availability of components. DOI: 10.13140/RG.2.2.12784.00004 .

Several theories propose that one of the core functions of inner speech (IS) is to support subjects in the completion of cognitively effortful tasks, especially those involving executive functions (EF). In this paper we focus on two populations who notoriously encounter difficulties in performing EF tasks, namely, people diagnosed with schizophrenia who experience auditory verbal hallucinations (Sz-AVH) and people within the Autism Spectrum Conditions (ASC). We focus on these two populations because they represent two different ways in which IS can (...) fail to help in EF tasks, which can be illustrative for other mental conditions. First, we review the main components of EF (Section 1). Then we explain the functions that IS is taken to perform in the domain of EF (Section 2) and review the evidence concerning problems about EF in the two populations of our study: Sz-AVH (Section 3) and ASC (Section 4). After this we further detail our account about what a properly functioning IS can do for both populations and how different IS profiles may impact EF performance: in the case of Sz-AVH, the uncontrolled and intrusive character of IS negatively affects EF performance, whereas in ASC, EF is not sufficiently supported by IS, given the tendency in this population to present a diminished use of IS (Section 5). We finally briefly discuss Attention Deficit/Hyperactivity Disorder (ADHD) and Developmental Language Disorders (DLD). (shrink)

This work stresses the importance of AI accountability to citizens and explores how a fourth independent government branch/institutions could be endowed to ensure that algorithms in today´s democracies convene to the principles of Constitutions. The purpose of this fourth branch of government in modern democracies could be to enshrine accountability of artificial intelligence development, including software-enabled technologies, and the implementation of policies based on big data within a wider democratic regime context. The work draws on Philosophy of Science, Political Theory (...) (Ethics and Ideas), as well as concepts derived from the study of democracy (responsibility and accountability) to make a theoretical analysis of what artificial intelligence (AI) means for the governance of society and what are the limitations of such type of AI governance. The discussion shows that human ideas, as cement of societies, make it problematic to enshrine governance of artificial intelligence into the world of devices. In ethical grounds, the work stresses an existing trade off between greater and faster advancement of technology, or innovation on the one hand, and human well being on the oher, where the later is not automatically guaranteed by default. This trade off is yet unresolved. The work contends that features of AI offer an opportunity to revise government priorities from a multilevel perspective, from the local to the upper levels. artificial intelligence, accountability, democracy, regulation, philosophy of science, ethics, political theory . (shrink)

A curious and comparatively neglected element of death penalty jurisprudence in America is my target in this paper. That element concerns the circumstances under which severely mentally disabled persons, incarcerated on death row, may have their sentences carried out. Those circumstances are expressed in a part of the law which turns out to be indefensible. This legal doctrine—competence-for-execution —holds that a condemned, death-row inmate may not be killed if, at the time of his scheduled execution, he lacks an (...) awareness of his impending death or the reasons for it. I argue that the law of CFE should be abandoned, along with the notion that it is permissible to kill the deeply disturbed just so long as they meet some narrow test of readiness to die. By adopting CFE, the courts have been forced to give independent conceptual and moral significance to a standard for competence that simply cannot bear the weight placed upon it. To be executable, CFE requires that a condemned prisoner meet a standard demonstrating an awareness of certain facts about his death. Yet this standard both leads to confusing and counter-intuitive results and is unsupported either by the reasons advanced by the courts on its behalf or by any of the standard theoretical justifications of criminal punishment. If executing the profoundly psychotic or delusional is wrong the law needs a better account of the wrong done when prisoners like Ford are killed. I suggest wherein that wrong might be located. (shrink)

Over the years, companies have adopted hiring algorithms because they promise wider job candidate pools, lower recruitment costs and less human bias. Despite these promises, they also bring perils. Using them can inflict unintentional harms on individual human rights. These include the five human rights to work, equality and nondiscrimination, privacy, free expression and free association. Despite the human rights harms of hiring algorithms, the AI ethics literature has predominantly focused on abstract ethical principles. This is problematic for two reasons. (...) First, AI principles have been criticized for being vague and not actionable. Second, the use of vague ethical principles to discuss algorithmic risks does not provide any accountability. This lack of accountability creates an algorithmic accountability gap. Closing this gap is crucial because, without accountability, the use of hiring algorithms can lead to discrimination and unequal access to employment opportunities. This paper makes two contributions to the AI ethics literature. First, it frames the ethical risks of hiring algorithms using international human rights law as a universal standard for determining algorithmic accountability. Second, it evaluates four types of algorithmic impact assessments in terms of how effectively they address the five human rights of job applicants implicated in hiring algorithms. It determines which of the assessments can help companies audit their hiring algorithms and close the algorithmic accountability gap. (shrink)

Fears of black-box algorithms are multiplying. Black-box algorithms are said to prevent accountability, make it harder to detect bias and so on. Some fears concern the epistemology of black-box algorithms in medicine and the ethical implications of that epistemology. In ‘Who is afraid of black box algorithms? On the epistemological and ethical basis of trust in medical AI,’ Juan Durán and Karin Jongsma seek to allay such fears. While we find some of their arguments compelling, we still see reasons for (...) fear. (shrink)

Cloud Computing is a developing field and lean toward by numerous one at current yet it's rage is part more rely upon its execution which thusly is excessively rely upon the powerful booking algorithm and load adjusting . In this paper we address this issue and propose an algorithm for private cloud which has high throughput and for open cloud which address the issue of condition awareness likewise with execution. To enhance the throughput in private cloud (...) SJF is utilized for planning and to conquer shape the issue of starvation we utilize limited pausing. For stack adjusting we screen the heap and dispatch the activity to the minimum stacked VM. To acquire advantage and to have open door for future upgrade out in the open cloud condition cognizance is the key factor and for better execution and load adjusting likewise wanted. While stack adjusting enhances the execution, the earth awareness increment the benefit of cloud suppliers. (shrink)

It is often said that the best system account of laws needs supplementing with a theory of perfectly natural properties. The ‘strength’ and ‘simplicity’ of a system is language-relative and without a fixed vocabulary it is impossible to compare rival systems. Recently a number of philosophers have attempted to reformulate the BSA in an effort to avoid commitment to natural properties. I assess these proposals and argue that they are problematic as they stand. Nonetheless, I agree with their aim, (...) and show that if simplicity is interpreted as ‘compression’, algorithmic information theory provides a framework for system comparison without the need for natural properties. (shrink)

Cross-linguistic strategies for mapping lexical and spatial relations from body partonym systems to external object meronymies (as in English ‘table leg’, ‘mountain face’) have attracted substantial research and debate over the past three decades. Due to the systematic mappings, lexical productivity and geometric complexities of body-based meronymies found in many Mesoamerican languages, the region has become focal for these discussions, prominently including contrastive accounts of the phenomenon in Zapotec and Tzeltal, leading researchers to question whether such systems should be explained (...) as global metaphorical mappings from bodily source to target holonym or as vector mappings of shape and axis generated “algorithmically”. I propose a synthesis of these accounts in this paper by drawing on the species-specific cognitive affordances of human upright posture grounded in the reorganization of the anatomical planes, with a special emphasis on antisymmetrical relations that emerge between arm-leg and face-groin antinomies cross-culturally. Whereas Levinson argues that the internal geometry of objects “stripped of their bodily associations” (1994: 821) is sufficient to account for Tzeltal meronymy, making metaphorical explanations entirely unnecessary, I propose a more powerful, elegant explanation of Tzeltal meronymic mapping that affirms both the geometric-analytic and the global-metaphorical nature of Tzeltal meaning construal. I do this by demonstrating that the “algorithm” in question arises from the phenomenology of movement and correlative body memories—an experiential ground which generates a culturally selected pair of inverse contrastive paradigm sets with marked and unmarked membership emerging antithetically relative to the transverse anatomical plane. These relations are then selected diagrammatically for the classification of object orientations according to systematic geometric iconicities. Results not only serve to clarify the case in question but also point to the relatively untapped potential that upright posture holds for theorizing the emergence of human cognition, highlighting in the process the nature, origins and theoretical validity of markedness and double scope conceptual integration. (shrink)

In this paper, I examine whether John Stuart Mill’s account of free speech can survive three main challenges posed by social media. First, I consider the problem of social media failing to distinguish between emotive and factual language. Second, I look at the problem of algorithms creating moralism. I then turn to a potential objection to my first two challenges. The objection elucidates the benefits of social media’s emotional and algorithmic character, amplifying arguments and increasing public engagement. However, I (...) take issue with this objection on consequentialist terms. I finally return to the third challenge, where I focus on how anonymity removes the consequences to our words; I contend that this final failure is the ultimate reason why Mill’s account cannot persist in the modern age. In conclusion, I argue that Mill’s account cannot withstand the problems posed by social media. (shrink)

Since approval of the EU General Data Protection Regulation (GDPR) in 2016, it has been widely and repeatedly claimed that the GDPR will legally mandate a ‘right to explanation’ of all decisions made by automated or artificially intelligent algorithmic systems. This right to explanation is viewed as an ideal mechanism to enhance the accountability and transparency of automated decision-making. However, there are several reasons to doubt both the legal existence and the feasibility of such a right. In contrast to the (...) right to explanation of specific automated decisions claimed elsewhere, the GDPR only mandates that data subjects receive meaningful, but properly limited, information (Articles 13-15) about the logic involved, as well as the significance and the envisaged consequences of automated decision-making systems, what we term a ‘right to be informed’. Further, the ambiguity and limited scope of the ‘right not to be subject to automated decision-making’ contained in Article 22 (from which the alleged ‘right to explanation’ stems) raises questions over the protection actually afforded to data subjects. These problems show that the GDPR lacks precise language as well as explicit and well-defined rights and safeguards against automated decision-making, and therefore runs the risk of being toothless. We propose a number of legislative and policy steps that, if taken, may improve the transparency and accountability of automated decision-making when the GDPR comes into force in 2018. (shrink)

When agents insert technological systems into their decision-making processes, they can obscure moral responsibility for the results. This can give rise to a distinct moral wrong, which we call “agency laundering.” At root, agency laundering involves obfuscating one’s moral responsibility by enlisting a technology or process to take some action and letting it forestall others from demanding an account for bad outcomes that result. We argue that the concept of agency laundering helps in understanding important moral problems in a (...) number of recent cases involving automated, or algorithmic, decision-systems. We apply our conception of agency laundering to a series of examples, including Facebook’s automated advertising suggestions, Uber’s driver interfaces, algorithmic evaluation of K-12 teachers, and risk assessment in criminal sentencing. We distinguish agency laundering from several other critiques of information technology, including the so-called “responsibility gap,” “bias laundering,” and masking. (shrink)

Let f(1)=2, f(2)=4, and let f(n+1)=f(n)! for every integer n≥2. Edmund Landau's conjecture states that the set P(n^2+1) of primes of the form n^2+1 is infinite. Landau's conjecture implies the following unproven statement Φ: card(P(n^2+1))<ω ⇒ P(n^2+1)⊆[2,f(7)]. Let B denote the system of equations: {x_j!=x_k: i,k∈{1,...,9}}∪{x_i⋅x_j=x_k: i,j,k∈{1,...,9}}. The system of equations {x_1!=x_1, x_1 \cdot x_1=x_2, x_2!=x_3, x_3!=x_4, x_4!=x_5, x_5!=x_6, x_6!=x_7, x_7!=x_8, x_8!=x_9} has exactly two solutions in positive integers x_1,...,x_9, namely (1,...,1) and (f(1),...,f(9)). No known system S⊆B with a finite (...) number of solutions in positive integers x_1,...,x_9 has a solution (x_1,...,x_9)∈(N\{0})^9 satisfying max(x_1,...,x_9)>f(9). For every known system S⊆B, if the finiteness/infiniteness of the set {(x_1,...,x_9)∈(N\{0})^9: (x_1,...,x_9) solves S} is unknown, then the statement ∃ x_1,...,x_9∈N\{0} ((x_1,...,x_9) solves S)∧(max(x_1,...,x_9)>f(9)) remains unproven. Let Λ denote the statement: if the system of equations {x_2!=x_3, x_3!=x_4, x_5!=x_6, x_8!=x_9, x_1 \cdot x_1=x_2, x_3 \cdot x_5=x_6, x_4 \cdot x_8=x_9, x_5 \cdot x_7=x_8} has at most finitely many solutions in positive integers x_1,...,x_9, then each such solution (x_1,...,x_9) satisfies x_1,...,x_9≤f(9). The statement Λ is equivalent to the statement Φ. It heuristically justifies the statement Φ . This justification does not yield the finiteness/infiniteness of P(n^2+1). We present a new heuristic argument for the infiniteness of P(n^2+1), which is not based on the statement Φ. Algorithms always terminate. We explain the distinction between existing algorithms (i.e. algorithms whose existence is provable in ZFC) and known algorithms (i.e. algorithms whose definition is constructive and currently known). Assuming that the infiniteness of a set X⊆N is false or unproven, we define which elements of X are classified as known. No known set X⊆N satisfies Conditions (1)-(4) and is widely known in number theory or naturally defined, where this term has only informal meaning. *** (1) A known algorithm with no input returns an integer n satisfying card(X)<ω ⇒ X⊆(-∞,n]. (2) A known algorithm for every k∈N decides whether or not k∈X. (3) No known algorithm with no input returns the logical value of the statement card(X)=ω. (4) There are many elements of X and it is conjectured, though so far unproven, that X is infinite. (5) X is naturally defined. The infiniteness of X is false or unproven. X has the simplest definition among known sets Y⊆N with the same set of known elements. *** Conditions (2)-(5) hold for X=P(n^2+1). The statement Φ implies Condition (1) for X=P(n^2+1). The set X={n∈N: the interval [-1,n] contains more than 29.5+\frac{11!}{3n+1}⋅sin(n) primes of the form k!+1} satisfies Conditions (1)-(5) except the requirement that X is naturally defined. 501893∈X. Condition (1) holds with n=501893. card(X∩[0,501893])=159827. X∩[501894,∞)= {n∈N: the interval [-1,n] contains at least 30 primes of the form k!+1}. We present a table that shows satisfiable conjunctions of the form #(Condition 1) ∧ (Condition 2) ∧ #(Condition 3) ∧ (Condition 4) ∧ #(Condition 5), where # denotes the negation ¬ or the absence of any symbol. No set X⊆N will satisfy Conditions (1)-(4) forever, if for every algorithm with no input, at some future day, a computer will be able to execute this algorithm in 1 second or less. The physical limits of computation disprove this assumption. (shrink)

I present a reading of EE 5.12/NE 6.12 according to which Aristotle argues for an executive account of φρόνησις (practical wisdom) to show why it is useful to possess this virtue. On this account, the practically wise person's actions are expressive of his knowledge of the fine, a knowledge that only the practically wise person has. This is why he must not only be a good deliberator, but also cunning (δεινότης), able to execute his actions well. An important (...) consequence of this reading is that the debate about whether Aristotle holds a Humean account of practical reason presupposes assumptions about the scope of rationality that Aristotle rejects. (shrink)

One of the main lines of research in algorithmic fairness involves individual fairness (IF) methods. Individual fairness is motivated by an intuitive principle, similar treatment, which requires that similar individuals be treated similarly. IF offers a precise account of this principle using distance metrics to evaluate the similarity of individuals. Proponents of individual fairness have argued that it gives the correct definition of algorithmic fairness, and that it should therefore be preferred to other methods for determining fairness. I argue (...) that individual fairness cannot serve as a definition of fairness. Moreover, IF methods should not be given priority over other fairness methods, nor used in isolation from them. To support these conclusions, I describe four in-principle problems for individual fairness as a definition and as a method for ensuring fairness: (1) counterexamples show that similar treatment (and therefore IF) are insufficient to guarantee fairness; (2) IF methods for learning similarity metrics are at risk of encoding human implicit bias; (3) IF requires prior moral judgments, limiting its usefulness as a guide for fairness and undermining its claim to define fairness; and (4) the incommensurability of relevant moral values makes similarity metrics impossible for many tasks. In light of these limitations, I suggest that individual fairness cannot be a definition of fairness, and instead should be seen as one tool among several for ameliorating algorithmic bias. (shrink)

Many artificial intelligence (AI) systems currently used for decision-making are opaque, i.e., the internal factors that determine their decisions are not fully known to people due to the systems’ computational complexity. In response to this problem, several researchers have argued that human decision-making is equally opaque and since simplifying, reason-giving explanations (rather than exhaustive causal accounts) of a decision are typically viewed as sufficient in the human case, the same should hold for algorithmic decision-making. Here, I contend that this argument (...) overlooks that human decision-making is sometimes significantly more transparent and trustworthy than algorithmic decision-making. This is because when people explain their decisions by giving reasons for them, this frequently prompts those giving the reasons to govern or regulate themselves so as to think and act in ways that confirm their reason reports. AI explanation systems lack this self-regulative feature. Overlooking it when comparing algorithmic and human decision-making can result in underestimations of the transparency of human decision-making and in the development of explainable AI that may mislead people by activating generally warranted beliefs about the regulative dimension of reason-giving. (shrink)

This dissertation examines aspects of the interplay between computing and scientific practice. The appropriate foundational framework for such an endeavour is rather real computability than the classical computability theory. This is so because physical sciences, engineering, and applied mathematics mostly employ functions defined in continuous domains. But, contrary to the case of computation over natural numbers, there is no universally accepted framework for real computation; rather, there are two incompatible approaches --computable analysis and BSS model--, both claiming to formalise algorithmic (...) computation and to offer foundations for scientific computing. -/- The dissertation consists of three parts. In the first part, we examine what notion of 'algorithmic computation' underlies each approach and how it is respectively formalised. It is argued that the very existence of the two rival frameworks indicates that 'algorithm' is not one unique concept in mathematics, but it is used in more than one way. We test this hypothesis for consistency with mathematical practice as well as with key foundational works that aim to define the term. As a result, new connections between certain subfields of mathematics and computer science are drawn, and a distinction between 'algorithms' and 'effective procedures' is proposed. -/- In the second part, we focus on the second goal of the two rival approaches to real computation; namely, to provide foundations for scientific computing. We examine both frameworks in detail, what idealisations they employ, and how they relate to floating-point arithmetic systems used in real computers. We explore limitations and advantages of both frameworks, and answer questions about which one is preferable for computational modelling and which one for addressing general computability issues. -/- In the third part, analog computing and its relation to analogue (physical) modelling in science are investigated. Based on some paradigmatic cases of the former, a certain view about the nature of computation is defended, and the indispensable role of representation in it is emphasized and accounted for. We also propose a novel account of the distinction between analog and digital computation and, based on it, we compare analog computational modelling to physical modelling. It is concluded that the two practices, despite their apparent similarities, are orthogonal. (shrink)

In order to fulfil their essential roles as the bearers of truth and the relata of logical relations, propositions must be public and shareable. That requirement has favoured Platonist and other nonmental views of them, despite the well-known problems of Platonism in general. Views that propositions are mental entities have correspondingly fallen out of favour, as they have difficulty in explaining how propositions could have shareable, objective properties. We revive a mentalist view of propositions, inspired by Artificial Intelligence work on (...) perceptual algorithms, which shows how perception causes persistent mental entities with shareable properties that allow them to fulfil the traditional roles of (one core kind of) propositions. The clustering algorithms implemented in perception produce outputs which are (implicit) atomic propositions in different minds. Coordination of them across minds proceeds by game-theoretic processes of communication. The account does not rely on any unexplained notions such as mental content, representation, or correspondence (although those notions are applicable in philosophical analysis of the result). (shrink)

This work examines the development and performance of federal independent regulatory bodies in Canada in the period up to 1979, with particular attention to the operation of legislative schemes that include executive review and appeal powers. The author assesses the impact of the exercise of these powers on the administrative law process, and proposes new models for the generation, interpretation, implementation, review, and enforcement of regulatory policy. The study includes a series of representative case studies based on documentation and extensive (...) interviews with individuals drawn from government, agencies, and other parties, including counsel for public interest groups. This enables author, writing from her experience as a participant-observer embedded in the public interest legal sector, to draw on the experiences and perspectives of a broad range of participants in the regulatory process, including but not limited to those dealing with the regulated energy, transportation, communications, and foreign investment sectors. Legal principles identified as emergent in leading judicial decisions in administrative law are used to assess the powers and practices used in executive reviews and appeals. The author finds those powers and practices to be flawed and proposes changes. The proposed models are designed to accord with emerging legal principles and avoid flaws of the types identified in the review and appeal provisions. This work, written under contract with the Administrative Law Project of the Law Reform Commission of Canada, formed one part of a comprehensive study of administrative law at the federal level in Canada. (shrink)

The patient with Capgras’ syndrome claims that people very familiar to him have been replaced by impostors. I argue that this disorder is due to the destruction of a representation that the patient has of the mind of the familiar person. This creates the appearance of a familiar body and face, but without the familiar personality, beliefs, and thoughts. The posterior site of damage in Capgras’ is often reported to be the temporoparietal junction, an area that has a role in (...) the mindreading system, a connected system of cortical areas that allow us to attribute mental states to others. Just as the Capgras’ patient claims that that man is not his father, the patient with asomatognosia claims that his arm is not really his. A similar account applies here, in that a nearby brain area, the supramarginal gyrus, is damaged. This area works in concert with the temporoparietal junction and other areas to produce a large representation of a mind inside a body situated in an environment. Damage to the mind-representing part of this system (coupled with damage to executive processes in the prefrontal lobes) causes Capgras’ syndrome, whereas damage to the body-representing part of this system (also coupled with executive damage) causes asomatognosia. (shrink)

The moot point of the Western philosophical rhetoric about free will consists in examining whether the claim of authorship to intentional, deliberative actions fits into or is undermined by a one-way causal framework of determinism. Philosophers who think that reconciliation between the two is possible are known as metaphysical compatibilists. However, there are philosophers populating the other end of the spectrum, known as the metaphysical libertarians, who maintain that claim to intentional agency cannot be sustained unless it is assumed that (...) indeterministic causal processes pervade the action-implementation apparatus employed by the agent. The metaphysical libertarians differ among themselves on the question of whether the indeterministic causal relation exists between the series of intentional states and processes, both conscious and unconscious, and the action, making claim for what has come to be known as the event-causal view, or between the agent and the action, arguing that a sort of agent causation is at work. In this paper, I have tried to propose that certain features of both event-causal and agent-causal libertarian views need to be combined in order to provide a more defendable compatibilist account accommodating deliberative actions with deterministic causation. The ‘‘agent-executed-eventcausal libertarianism’’, the account of agency I have tried to develop here, integrates certain plausible features of the two competing accounts of libertarianism turning them into a consistent whole. I hope to show in the process that the integration of these two variants of libertarianism does not challenge what some accounts of metaphysical compatibilism propose—that there exists a broader deterministic relation between the web of mental and extra-mental components constituting the agent’s dispositional system—the agent’s beliefs, desires, short-term and long-term goals based on them, the acquired social, cultural and religious beliefs, the general and immediate and situational environment in which the agent is placed, etc. on the one hand and the decisions she makes over her lifetime on the basis of these factors. While in the ‘‘Introduction’’ the philosophically assumed anomaly between deterministic causation and the intentional act of deciding has been briefly surveyed, the second section is devoted to the task of bridging the gap between compatibilism and libertarianism. The next section of the paper turns to an analysis of folk-psychological concepts and intuitions about the effects of neurochemical processes and prior mental events on the freedom of making choices. How philosophical insights can be beneficially informed by taking into consideration folk-psychological intuitions has also been discussed, thus setting up the background for such analysis. It has been suggested in the end that support for the proposed theory of intentional agency can be found in the folk-psychological intuitions, when they are taken in the right perspective. (shrink)

Bedau's influential (1997) account analyzes weak emergence in terms of the non-derivability of a system’s macrostates from its microstates except by simulation. I offer an improved version of Bedau’s account of weak emergence in light of insights from information theory. Non-derivability alone does not guarantee that a system’s macrostates are weakly emergent. Rather, it is non-derivability plus the algorithmic compressibility of the system’s macrostates that makes them weakly emergent. I argue that the resulting information-theoretic picture provides a metaphysical (...) account of weak emergence rather than a merely epistemic one. (shrink)

Existing accounts of shared intention do not claim that a single token of intention can be jointly framed and executed by multiple agents; rather, they claim that multiple agents can frame distinct, individual intentions in such a way as to qualify as jointly intending something. In this respect, the existing accounts do not show that intentions can be shared in any literal sense. This article argues that, in failing to show how intentions can be literally shared, these accounts fail to (...) resolve what seems problematic in the notion of shared intention. It then offers an account in which the problem of shared intention is resolved, because intention can indeed be literally shared. This account is derived from Margaret Gilbert's notion of a "pool of wills," to which it applies Searle's definition of intention. (shrink)

Ludwig Wittgenstein, in the "Remarks on the Foundation of Mathematics", often refers to contradictions as deserving special study. He is said to have predicted that there will be mathematical investigations of calculi containing contradictions and that people will pride themselves on having emancipated themselves from consistency. This paper examines a way of taking this prediction seriously. It starts by demonstrating that the easy way of understanding the role of contradictions in a discourse, namely in terms of pure convention within a (...) specific linguistic community, is naive and therefore to be avoided. A number of steps will then be taken to formulate and justify what will be called a ‘containment-account’ of contradiction. This term refers to a way of understanding how a contradiction in a discourse can be contained without allowing it to infect the entire discourse with inconsistency. The account builds on work done by N. Rescher and involves complex ontologies that are either over-determined or under-determined at some points. These worlds are such that, for some P, they allow us to deny simultaneously both that P and that -P. They likewise allow us to hold both that P and that -P. The ontological status of P and that of -P are considered independent issues, so as to block the inference from P and -P to the conjunction (P & -P). In this way, the task of containment is carried out by the complexity of the ontology determining the possible worlds under consideration. The paper proceeds by countering the objection that such possible worlds are useless fictions. This is carried out by highlighting three significant areas of application, one in philosophy of science, one in philosophy of religion, and one in the area of epistemology. In general, one may say that, in some language-games, a contradiction can be a useful instrument to attest that rationality goes beyond ratiocination, in other words to indicate that there is more to discourse and practice than what can be expressed in precise algorithmic trees. The upshot of the entire argument is that the proposed ‘containment-account’ of contradiction can be an adequate illustration of how Wittgenstein’s prediction is not sterile, but a possible source of inspiration. (shrink)

Accountability for corporate social responsibility (CSR) and its societal challenges is undetermined, and it is unclear whether business or society should carry these responsibilities. Despite severe criticism from some, many organizations continue to invest in and promote CSR. The purpose of this multiple-case study was to increase the understanding of the phenomenon from the perspective of a purposeful sample of participants who contribute to CSR execution and who were representatives of the 10 organizations identified as active promoters. The participant (...) corporations (case studies), in Europe and North America, were mainly in the telecommunications industry. Study data came from 11 face-to-face, semistructured interviews with chief executive officers (CEOs) and other CSR key participants, a review of corporate archival records, and a review of other sources regarding the effective implementation of CSR in these organizations. The conceptual framework consisted of Carroll’s constructs of CSR based on economic, legal, social, and discretionary elements. The constant comparative method was used to analyze the interview data and identify factors leading corporations to continue to engage in CSR. These factors were economic, social impact, legal compliance, or good reputation, sponsored by transformational or adaptive leaderships and endorsed by visionary CEOs. The findings may enlighten and motivate other organizations to engage in CSR programs and connect stakeholders’ contribution to a broadened positive social change. (shrink)

Software patents are commonly criticised for being fuzzy, context-sensitive, and often granted for trivial inventions. More often than not, these shortcomings are said to be caused by the abstract nature of software - with little further analysis offered. Drawing on Plato’s Parmenides, this paper will argue (1) that the reason why software patents seem to be elusive is that patent law suggests to think about algorithms as paradigmatic examples and (2) that Plato’s distinction between two modes of predication and the (...) role of competence in his account of knowledge are helpful not only for conceptualising knowledge of algorithms, but also for understanding the limits of software patent regimes. (shrink)

This article offers a Nietzschean theory of digital will to power to conceptualize the temporality of social media feeds run by algorithms. Stylistic and methodological temporalities of Nietzsche are discussed as well as their influence in subsequent social theory of political technologies. The paradox of heavy investment in both subjective expression and nonhuman temporalization in social media milieus is addressed with the concept of an event-without-witness drawn from Nietzsche’s account of himself as the solitary thinker of catastrophe of nihilism (...) and psychoanalytical and deconstructive literatures on the catastrophes of the 20th century. Nietzsche’s fundamental resistance to and fascination with the philosophical and cultural modes of mummyfication, i.e. eternalization as an expression of the will to power is used to think the will to power in the creative algorithmic temporalization of social interactions through the selection, distribution and serialization of data for social media feeds. (shrink)

The Computational Theory of Mind (CTM) holds that cognitive processes are essentially computational, and hence computation provides the scientific key to explaining mentality. The Representational Theory of Mind (RTM) holds that representational content is the key feature in distinguishing mental from non-mental systems. I argue that there is a deep incompatibility between these two theoretical frameworks, and that the acceptance of CTM provides strong grounds for rejecting RTM. The focal point of the incompatibility is the fact that representational content is (...) extrinsic to formal procedures as such, and the intended interpretation of syntax makes no difference to the execution of an algorithm. So the unique 'content' postulated by RTM is superfluous to the formal procedures of CTM. And once these procedures are implemented in a physical mechanism, it is exclusively the causal properties of the physical mechanism that are responsible for all aspects of the system's behaviour. So once again, postulated content is rendered superfluous. To the extent that semantic content may appear to play a role in behaviour, it must be syntactically encoded within the system, and just as in a standard computational artefact, so too with the human mind/brain - it's pure syntax all the way down to the level of physical implementation. Hence 'content' is at most a convenient meta-level gloss, projected from the outside by human theorists, which itself can play no role in cognitive processing. (shrink)

We present an algorithm for concept combination inspired and informed by the research in cognitive and experimental psychology. Dealing with concept combination requires, from a symbolic AI perspective, to cope with competitive needs: the need for compositionality and the need to account for typicality effects. Building on our previous work on weighted logic, the proposed algorithm can be seen as a step towards the management of both these needs. More precisely, following a proposal of Hampton [1], it (...) combines two weighted Description Logic formulas, each defining a concept, using the following general strategy. First it selects all the features needed for the combination, based on the logical distinc- tion between necessary and impossible features. Second, it determines the threshold and assigns new weights to the features of the combined concept trying to preserve the relevance and the necessity of the features. We illustrate how the algorithm works exploiting some paradigmatic examples discussed in the cognitive literature. (shrink)

Synthetic biology aims at reconstructing life to put to the test the limits of our understanding. It is based on premises similar to those which permitted invention of computers, where a machine, which reproduces over time, runs a program, which replicates. The underlying heuristics explored here is that an authentic category of reality, information, must be coupled with the standard categories, matter, energy, space and time to account for what life is. The use of this still elusive category permits (...) us to interact with reality via construction of self-consistent models producing predictions which can be instantiated into experiments. While the present theory of information has much to say about the program, with the creative properties of recursivity at its heart, we almost entirely lack a theory of the information supporting the machine. We suggest that the program of life codes for processes meant to trap information which comes from the context provided by the environment of the machine. (shrink)

In a world that is overflowing with journals and other outlets for scientific publication, the appearance of any new periodical requires some justification. There are already more journals than we can read and more conferences than we can attend. In the case of applied Ontology, we believe that the creation of anew journal not only is completely justifiable, it is downright exciting. For too long, workers in computer science have assumed that content comes for free. “Theory” in computer science has (...) always meant the theory of processes and of computation. We measure the complexity of computer programs in terms of how long it takes machines to execute them, not in terms of how long it takes people to understand and to represent the data on which those programs might operate. We typically describe computer code in terms of algorithms that operate on formal parameters, often without pausing to discuss where the data that might satisfy those parameters come from. This journal was founded on the premise that workers in computer science, informatics, and information science are overdue in paying as much attention to contents as they do to algorithms. (shrink)

I offer an account of the experience of acting that demonstrates how agentive aspects of experience associated with the execution of intentions are richly integrated with perceptual aspects associated with parts of action taking place in the publicly observable world. On the view I elucidate, the experience of acting is often both an engagement with the world and a type of intimate acquaintance with it. In conscious action the agent consciously intervenes in the world and consciously experiences the (...) world she is changing. In section one, I discuss extant accounts of the experience of acting, noting deficiencies. In sections two and three, I develop my own account, drawing on Casey O’Callaghan’s work on multi-modal perception. In the conclusion, I discuss ramifications for psychology and philosophy. (shrink)

We overview logical and computational explanations of the notion of tractability as applied in cognitive science. We start by introducing the basics of mathematical theories of complexity: computability theory, computational complexity theory, and descriptive complexity theory. Computational philosophy of mind often identifies mental algorithms with computable functions. However, with the development of programming practice it has become apparent that for some computable problems finding effective algorithms is hardly possible. Some problems need too much computational resource, e.g., time or memory, to (...) be practically computable. Computational complexity theory is concerned with the amount of resources required for the execution of algorithms and, hence, the inherent difficulty of computational problems. An important goal of computational complexity theory is to categorize computational problems via complexity classes, and in particular, to identify efficiently solvable problems and draw a line between tractability and intractability. -/- We survey how complexity can be used to study computational plausibility of cognitive theories. We especially emphasize methodological and mathematical assumptions behind applying complexity theory in cognitive science. We pay special attention to the examples of applying logical and computational complexity toolbox in different domains of cognitive science. We focus mostly on theoretical and experimental research in psycholinguistics and social cognition. (shrink)

I here defend an account of the will as practical reason —or, using Kant's phrase, as " reason in its practical employment"—as against a view of the will as a capacity for choice, in addition to reason, by which we execute practical judgments in action. Certain commonplaces show distance between judgment and action and thus seem to reveal the need for a capacity, in addition to reason, by which we execute judgment in action. However, another ordinary fact pushes in (...) the other direction: the activities of the will are activities for which the person is answerable in a very particular sort of way. This answerability is most easily understood if willing involves settling a question. Settling a question seems to be a capacity of reason. Thus it can seem that activities of will are activities of our capacity for reasoning. I will suggest that we can accommodate the commonplaces while still understanding the will as reason in its practical employment, by abandoning the assumption that practical reasoning concludes in a judgment. Rather, reasoning which concludes in a judgment—reasoning directed at the question of whether p—is theoretical reasoning. In its practical employment, reason is directed at the question of whether to x; it concludes, not in a judgment about x-ing, but rather in an intention to x. (shrink)

This paper addresses the field of economic measurements of the value of assets, carried out by the methods of independent expert evaluation. The mathematical principles of application, within a comparative methodical approach, of additive and multiplicative models for correcting the cost of single indicator of compared objects have been considered. The differences of mathematical basis of the compared models were analyzed. It has been shown that the ambiguity in the methodology of correction procedure requires studying the advantages and disadvantages of (...) known models, as well as the justification and elaboration of recommendations for their application. Possible forms of correction representation using several alternative units of measurement have been defined; formulas for their interconnection have been built. Analytic expressions have been derived that mathematically describe the algorithms for performing the evaluation correction procedure using various forms of correction representation. The influence of the correction execution model on the characteristics of uncertainty in the independent evaluation result has been analyzed. The scope of two possible types of correction introduction models has been determined. A specific numerical example was used to demonstrate the methodological advantages of using a multiplicative model when summarizing percentage corrections. The independence of the correction result on the sequence of correction introduction has been confirmed. It is proposed to use the selected measure of partial corrections as a criterion for the adequacy of the correction introduction model. It is proved that the result of the independent expert evaluation depends on the chosen model and does not depend on the sequence of correction introduction. The reported study results are important in terms of theory and practice since they make it possible to improve the accuracy and reliability of the result of independent expert evaluation. (shrink)