Mikko Siponen

The relevance of different concepts of computer software (henceforth SW) rights is analysed from the viewpoint of divergent sociopolitical doctrines. The question of software rights is considered from the ontological assumptions, on one extreme, to the relevance of current practical applications of SW rights (such as copyright and patent), on the other extreme. It will be argued (from a non-descriptive/non-cognitive account) that the current expression of SW rights in Western societies (namely copyright, excluding patent) can be seen to be fair from the viewpoint of the theses of agreed rights and universalisability. Finally, given that such practice is neither immoral, nor irrelevant-but fair (based on the ad ignorantiam argument)-we have good reason to respect it rather than violate or demolish it

Computer users copy computer software - this is well-known. However, less well-known are the reasons why some computer users choose to make unauthorized copies of computer software. Furthermore, the relationship linking the theory and the practice is unknown, i.e., how the attitudes of ordinary end-users correspond with the theoretical views of computer ethics scholars. In order to fill this gap in the literature, we investigated the moral attitudes of 249 Finnish computing students towards the unauthorized copying of computer software, and we then asked how these results compared with the theoretical reasons offered by computer ethics scholars. The results shed a new light on students' moral attitudes with respect to the unauthorized copying of software. In particular, this new knowledge is useful for computer ethics teachers, and for organizations seeking to combat this practice.

It has been debated whether unauthorized copying of computer software is morally justified and whether developers or software companies can own software and require users to pay for its use. Four views in favour of unauthorized copying of software can be distinguished: 'free software', the landlord analogy, the 'non-exclusiveness argument' and 'it is justified to copy a program that we would never buy'. Considerations regarding these issues can be retraced to the three foundations of rights: inherited rights that are already in place, agreed rights, and no rights. From the viewpoint of agreed rights, rights are based on agreement and negotiation, and, referring to the universalizability theses by Rawls and Hare, I argue that it is justified that developers or software companies 'own' their software. I discuss the economic and social effects of free SW, understood as the abolition of financial acknowledgements, suggested by Stallman. I conclude that such free software would give rise to socio-political changes toward systems that are something other than liberal-based. Again, I argue that we have a reason to object to Stallman's program in the light of the universalizability theses. Nevertheless, even if one were to perceive this as a convincing goal, it is questionable whether one should make unauthorized copies on these grounds in a society that does not function on such lines: one should first seek to change the norms and practices of one's society. This is further argued to be advisable, since it is not obvious that adhering to software copyright in the general sense is unfair or irrelevant. For these reasons, we should take violation of the laws governing software copying seriously. Finally, I criticize the non-exclusiveness argument, the landlord analogy and the view that 'is it justified to copy a program that we would never buy'.

Positivism has been used to establish a standard that Information Systems (IS) research must meet to be scientific. According to such positivistic beliefs in IS, scientific research should: 1) be generalizable, 2) focus on stable independent variables, 3) have certain ontological assumptions, and 4) use statistical or quantitative methods rather than qualitative methods. We argue that logical positivist philosophers required none of these. On the contrary, logical positivist philosophers regarded philosophizing in general and ontological considerations in particular as nonsense. Moreover, the positivists’ preferred empirical research method was not a survey, but rather a qualitative observation recorded by field notes. In addition, positivist philosophers required neither statistical nor nonstatistical generalizability. At least some positivist philosophers also acknowledged the study of singular cases as being scientific. Many research orientations (e.g., single-setting research, examination of change, qualitative research) that are deemed “unscientific” by positivism in IS seem to be “scientific” (in principle) according to logical positivism. In turn, generally speaking, what has been justified as scientific by positivism in IS (e.g., requirements of statistical or nonstatistical generalizability, surveys, independent variables, ontological views) were either not required by logical positivists or were regarded as nonsensical by logical positivists. Furthermore, given that positivism is sometimes associated (or confused) with logical empiricism in IS, we also briefly discuss logical empiricism. Finally, realizing that certain influential, taken-forgranted assumptions that underlie IS research are unwarranted could have ground-breaking implications for future IS research.

It is well known that girls are not interested in computer science, information systems, and software engineering studies. While the underlying reasons for this phenomenon have been studied in the US, Canada, and Australia, only a few studies have been carried out in Europe and in Scandinavia. To fill this gap in the research, we have analyzed the qualitative responses of 64 female sixth form students concerning their attitudes towards studying information technology, including computer science, information systems, and software engineering disciplines, and their views about IT as a profession. The results suggest that the IT field is seen in quite a positive light by the girls. Although many of the respondents do not consider IT to be their profession, they nevertheless have positive attitudes towards the field. According to the respondents, the field is growing and developing; it is respected, and seen as the field of the future. Girls who want to become IT professionals see that the profession entails good employment possibilities and benefits and is respected. Some girls have negative views towards the field. These views illustrate the underlying reasons why these girls do not want to study IT. The girls did not perceive the field to be human-related. The need for skills in mathematics and physics are also listed as key reasons why some girls do not want to become IT students. The results of the study suggest that there is a need to clarify among sixth form students the fact that IT jobs can be divided into computer science, information systems, and software engineering, all of which require different competences.

The philosophy of mechanisms has developed rapidly during the last 30 years. As mechanisms-based explanations are often seen as an alternative to nomological, law-based explanations, MBEs could be relevant in IS. We begin by offering a short history of mechanistic philosophy and set out to clarify the contemporary landscape. We then suggest that mechanistic models provide an alternative to variance and process models in IS. Finally, we highlight how MBEs typically contain deliberate misrepresentations. Although MBEs have recently been advocated as critical realist accounts in IS, idealizations seem to violate some fundamental tenets of CR and research method principles for CR. Idealizations in MBEs, therefore, may risk being regarded as flawed in IS. If it turns out that CR cannot account for idealizations, naturalism can, and it does so without extra-philosophical baggage.

We respond to Lee’s (forthcoming) commentary on our article “Demystifying the Influential IS Legends of Positivism” (Siponen & Tsohou [S&T], 2018). Lee offers four arguments against our analyses and conclusions in S&T (2018). First, because logical positivism (LP) has been discredited, he contends it cannot be used as a normative standard in IS. We clarify that our conclusions in S&T (2018) point to (1) the lack of justification for certain IS beliefs, and (2) a misunderstanding rather than legitimacy of LP as a philosophy of science. Second, Lee argues that IS researchers characterizing positivism never said they were following the tenets of LP. We provide evidence to show some influential papers on positivism in IS research indicated they were indeed following LP. Third, Lee offers an alternative explanation for the emergence and nature of IS positivism. His explanation has merit, and it can be accommodated in S&T’s (2018) account of positivism in IS. Unfortunately, his explanation does not account for certain problems in the IS discipline’s use of positivism. In S&T (2018), we provide a plausible explanation for these problems. Finally, we discuss the implications of S&T’s (2018) findings for the need to better understand the philosophical assumptions underlying “IS positivism.” We also counter Lee’s arguments that our conclusions in S&T (2018) should not make a difference to the future of IS research.

Numerous articles in top IS journals note as a limitation and lack of generalizability that their findings are specific to a certain type of technology, culture, and so on. We argue that this generalizability concern is about limited scope. The IS literature notes this preference for generalizability as a characteristic of good science and it is sometimes confused with statistical generalizability. We argue that such generalizability can be in conflict with explanation or prediction accuracy. An increase in scope can decrease explanation or prediction accuracy. Thus, in sciences such as cancer research, where explanation and prediction accuracy are highly valued, the cancer accounts have become increasingly narrower. IS thinking has not yet benefitted from these considerations. Whether generalizability is valued should be linked with the research aims. If the aim is practical applicability through explanation or prediction accuracy, then “limited” generalizability could be a strength rather than a weakness.

Guidelines for different qualitative research genres have been proposed in information systems. As these guidelines are outlined for conducting and evaluating good research, studies may be denied publication simply because they do not follow a prescribed methodology. This can result in “checkbox” compliance, where the guidelines become more important than the study. We argue that guidelines can only be used to evaluate what good research is if there is evidence that they lead to certain good research outcomes. Currently, the guidelines do not present such evidence. Instead, when it is presented, the evidence is often an authority argument or evidence of popularity with usability examples. We further postulate that such evidence linking guidelines and outcomes cannot be presented. Therefore, it may be time for the IS research community to acknowledge that many research method principles we regard as authoritative may ultimately be based on speculation and opinion, and thus, they should be taken less seriously as absolute guidelines in the review process.

Specialisation, by seeking theoretically deeper explanations or more accurate predictions, is common in the sciences. It typically involves splitting, where one model is further divided into several or even hundreds of narrow-scope models. The Information Systems (IS) literature does not discuss such splitting. On the contrary, many seminal IS studies report that a narrow scope is less strong, less interesting, or less useful than a wider scope. In this commentary, we want to raise the awareness of the IS community that in modern scientific progress, specialisation – an activity that generally narrows the scope and decreases the generalisability of a hypothesis – is important. The philosophy of science discusses such positive developments as splitting and trading off a wide scope in favour of accuracy. Narrowing the scope may increase value, especially in sciences where practical applicability is valued. If the IS community generally prefers a wider scope, then we run the risk of not having the information necessary to understand IS phenomena in detail. IS research must understand splitting, how it results in narrowing the scope, and why it is performed for exploratory or predictive reasons in variance, process, and stage models.