[How] Can Pluralist Approaches to Computational Cognitive Modeling of Human Needs and Values Save our Democracies?

In our increasingly digital societies, many companies have business models that perceive users’ (or customers’) personal data as a siloed resource, owned and controlled by the data controller rather than the data subjects. Collecting and processing such a massive amount of personal data could have many negative technical, social and economic consequences, including invading people’s privacy and autonomy. As a result, regulations such as the European General Data Protection Regulation (GDPR) have tried to take steps towards a better implementation of the right to digital privacy. This paper proposes that such legal acts should be accompanied by the development of complementary technical solutions such as Cognitive Personal Assistant Systems to support people to effectively manage their personal data processing on the Internet. Considering the importance and sensitivity of personal data processing, such assistant systems should not only consider their owner’s needs and values, but also be transparent, accountable and controllable. Pluralist approaches in computational cognitive modelling of human needs and values which are not bound to traditional paradigmatic borders such as cognitivism, connectionism, or enactivism, we argue, can create a balance between practicality and usefulness, on the one hand, and transparency, accountability, and controllability, on the other, while supporting and empowering humans in the digital world. Considering the threat to digital privacy as significant to contemporary democracies, the future implementation of such pluralist models could contribute to power-balance, fairness and inclusion in our societies

HUMAN-AI COLLABORATION IN ORGANISATIONS: A LITERATURE REVIEW ON ENABLING VALUE CREATION

The augmentation of human intellect and capability with artificial intelligence is integral to the advancement of next generation human-machine collaboration technologies designed to drive performance improvement and innovation. Yet we have limited understanding of how organisations can translate this potential into creating sustainable business value. We conduct an in-depth literature review of interdisciplinary research on the challenges and opportunities in organisational adoption of human-AI collaboration for value creation. We identify five positions central to how organisations can integrate and align the socio-technical challenges of augmented collaboration, namely strategic positioning, human engagement, organisational evolution, technology development and intelligence building. We synthesise the findings by means of an integrated model that focuses organisations on building the requisite internal microfoundations for the systematic management of augmented systems

Tokens Matter

During the global pandemic, information workers were abruptly forced to engage in virtual work. This paper reports on an experiment seeking to formalize the formalization of small team coordination at London Blockchain Lab through the use of blockchain-supported tokenization. The Web3 organizing vision promotes the technology as an enabler of new ways for individuals and organizations to engage in the transparent exchange of scarce digital rights. However, little attention has been paid to the use of blockchain technologies to coordinate distributed collaborative activities. This paper seeks to understand the viability of this vision amongst a community of expected early adopters through design experimentation resulting in interview data. The study points towards the significant gap between the Web3 vision and the problems of realizing this in practice. This highlights fundamental barriers to using blockchain for team collaboration while also pointing toward its potential. Even the most willing and able find it hard to turn code into law through tokenizing collaboration

mHealth Research Applied to Regulated and Unregulated Behavioral Health Sciences

Behavioral scientists are developing new methods and frameworks that leverage mobile health technologies to optimize individual level behavior change. Pervasive sensors and mobile apps allow researchers to passively observe human behaviors “in the wild” 24/7 which supports delivery of personalized interventions in the real-world environment. This is all possible because these technologies contain an incredible array of sensors that allow applications to constantly record user location and can contextualize current environmental conditions through barometers, thermometers, and ambient light sensors and can also capture audio and video of the user and their surroundings through multiple integrated high-definition cameras and microphones. These tools are a game changer in behavioral health research and, not surprisingly, introduce new ethical, regulatory/legal and social implications described in this article

Reinventing discovery learning: a field-wide research program

© 2017, Springer Science+Business Media B.V., part of Springer Nature. Whereas some educational designers believe that students should learn new concepts through explorative problem solving within dedicated environments that constrain key parameters of their search and then support their progressive appropriation of empowering disciplinary forms, others are critical of the ultimate efficacy of this discovery-based pedagogical philosophy, citing an inherent structural challenge of students constructing historically achieved conceptual structures from their ingenuous notions. This special issue presents six educational research projects that, while adhering to principles of discovery-based learning, are motivated by complementary philosophical stances and theoretical constructs. The editorial introduction frames the set of projects as collectively exemplifying the viability and breadth of discovery-based learning, even as these projects: (a) put to work a span of design heuristics, such as productive failure, surfacing implicit know-how, playing epistemic games, problem posing, or participatory simulation activities; (b) vary in their target content and skills, including building electric circuits, solving algebra problems, driving safely in traffic jams, and performing martial-arts maneuvers; and (c) employ different media, such as interactive computer-based modules for constructing models of scientific phenomena or mathematical problem situations, networked classroom collective “video games,” and intercorporeal master–student training practices. The authors of these papers consider the potential generativity of their design heuristics across domains and contexts