Scaling up analogical innovation with crowds and AI

Kittur, Aniket; Yu, Lixiu; Hope, Tom; Chan, Joel; Lifshitz-Assaf, Hila; Gilon, Karni; Ng, Felicia; Kraut, Robert E.; Shahaf, Dafna

doi:10.1073/pnas.1807185116

Cited by 56 publications

(31 citation statements)

References 44 publications

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“…Scientific methods from the areas of game theory, mechanism design, incentive design, socio-technical optimization and learning [41][42][43][44] are becoming applicable to further support sustainability movements in society. Methods such as the ones of this work and a transdisciplinary scientific approach are required to improve and accelerate the development of sustainability knowledge-bases, using responsible AI and the wisdom of crowds [45,46].…”

Section: Discussion and Outlookmentioning

confidence: 99%

How value-sensitive design can empower sustainable consumption

et al. 2021

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In a so-called overpopulated world, sustainable consumption is of existential importance. However, the expanding spectrum of product choices and their production complexity challenge consumers to make informed and value-sensitive decisions. Recent approaches based on (personalized) psychological manipulation are often intransparent, potentially privacy-invasive and inconsistent with (informational) self-determination. By contrast, responsible consumption based on informed choices currently requires reasoning to an extent that tends to overwhelm human cognitive capacity. As a result, a collective shift towards sustainable consumption remains a grand challenge. Here, we demonstrate a novel personal shopping assistant implemented as a smart phone app that supports a value-sensitive design and leverages sustainability awareness, using experts’ knowledge and ‘wisdom of the crowd’ for transparent product information and explainable product ratings. Real-world field experiments in two supermarkets confirm higher sustainability awareness and a bottom-up behavioural shift towards more sustainable consumption. These results encourage novel business models for retailers and producers, ethically aligned with consumer preferences and with higher sustainability.

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Section: Discussion and Outlookmentioning

confidence: 99%

How value-sensitive design can empower sustainable consumption

et al. 2021

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“…In addition, technological advancements require ongoing attention to identify the potential for new research technologies like artificial intelligence and their implementation for OIS practices. For example, as discussed above, pioneering advances can already be observed in the area of computational citizen science, as well as in the creation of hybrid Open Science processes combining experts, crowds, and AI (Kittur et al 2019).…”

Section: Future Research On Open Innovation In Science (Ois)mentioning

confidence: 99%

The Open Innovation in Science research field: a collaborative conceptualisation approach

Beck

Bergenholtz

Bogers

et al. 2020

Industry and Innovation

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130

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Openness and collaboration in scientific research are attracting increasing attention from scholars and practitioners alike. However, a common understanding of these phenomena is hindered by disciplinary boundaries and disconnected research streams. We link dispersed knowledge on Open Innovation, Open Science, and related concepts such as Responsible Research and Innovation by proposing a unifying Open Innovation in Science (OIS) Research Framework. This framework captures the antecedents, contingencies, and consequences of open and collaborative practices along the entire process of generating and disseminating scientific insights and translating them into innovation. Moreover, it elucidates individual-, team-, organisation-, field-, and society-level factors shaping OIS practices. To conceptualise the framework, we employed a collaborative approach involving 47 scholars from multiple disciplines, highlighting both tensions and commonalities between existing approaches. The OIS Research Framework thus serves as a basis for future research, informs policy discussions, and provides guidance to scientists and practitioners.

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“…17 Similarly, the platform Science at Home initially used crowds to help solve problems in quantum physics (Jensen et al 2021) but has now started to additionally investigate crowd members' human problem solving as a core area of research -creating new ambiguities regarding the role of citizens as active participants in research vs. study subjects (see Section 3.3). 18 Finally, problem solving using analogies has long been considered too difficult for algorithms but recent research demonstrates that hybrid systems combining crowds and machines can leverage the respective strengths of both actors (Kittur et al 2019).…”

Section: From Tool To Third Actor: the Rise Of Machinesmentioning

confidence: 99%

Crowds, citizens, and science: a multi-dimensional framework and agenda for future research

Franzoni

Poetz

Sauermann

2021

Industry and Innovation

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Research projects that actively involve 'crowds' or non-professional 'citizen scientists' are attracting growing attention. Such projects promise to increase scientific productivity while also connecting science with the general public. We make three contributions. First, we argue that the largely separate literatures on 'Crowd Science' and 'Citizen Science' investigate strongly overlapping sets of projects but take different disciplinary lenses. Closer integration can enrich research on Crowd and Citizen Science (CS). Second, we propose a framework to profile projects with respect to four types of crowd contributions: activities, knowledge, resources, and decisions. This framework also accommodates machines and algorithms, which increasingly complement or replace professional and non-professional researchers as a third actor. Finally, we outline a research agenda anchored on important underlying organisational challenges of CS projects. This agenda can advance our understanding of Crowd and Citizen Science, yield practical recommendations for project design, and contribute to the broader organisational literature.

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Scaling up analogical innovation with crowds and AI

Cited by 56 publications

References 44 publications

How value-sensitive design can empower sustainable consumption

How value-sensitive design can empower sustainable consumption

The Open Innovation in Science research field: a collaborative conceptualisation approach

Crowds, citizens, and science: a multi-dimensional framework and agenda for future research

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