research-article

Open access

Power to the People? Opportunities and Challenges for Participatory AI

Authors:

Vinodkumar Prabhakaran,

Madeleine Clare Elish,

Shakir MohamedAuthors Info & Claims

EAAMO '22: Proceedings of the 2nd ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization

Article No.: 6, Pages 1 - 8

https://doi.org/10.1145/3551624.3555290

Published: 17 October 2022 Publication History

Abstract

Participatory approaches to artificial intelligence (AI) and machine learning (ML) are gaining momentum: the increased attention comes partly with the view that participation opens the gateway to an inclusive, equitable, robust, responsible and trustworthy AI. Among other benefits, participatory approaches are essential to understanding and adequately representing the needs, desires and perspectives of historically marginalized communities. However, there currently exists lack of clarity on what meaningful participation entails and what it is expected to do. In this paper we first review participatory approaches as situated in historical contexts as well as participatory methods and practices within the AI and ML pipeline. We then introduce three case studies in participatory AI. Participation holds the potential for beneficial, emancipatory and empowering technology design, development and deployment while also being at risk for concerns such as cooptation and conflation with other activities. We lay out these limitations and concerns and argue that as participatory AI/ML becomes in vogue, a contextual and nuanced understanding of the term as well as consideration of who the primary beneficiaries of participatory activities ought to be constitute crucial factors to realizing the benefits and opportunities that participation brings.

References

[1]

Ifeoma Ajunwa. 2019. An Auditing Imperative for Automated Hiring. (2019).

[2]

Miguel Arana-Catania, Felix-Anselm Van Lier, Rob Procter, Nataliya Tkachenko, Yulan He, Arkaitz Zubiaga, and Maria Liakata. 2021. Citizen participation and machine learning for a better democracy. arXiv preprint arXiv:2103.00508(2021).

[3]

Sherry R Arnstein. 1969. A ladder of citizen participation. Journal of the American Institute of planners 35, 4 (1969), 216–224.

[4]

Peter M Asaro. 2000. Transforming society by transforming technology: the science and politics of participatory design. Accounting, Management and Information Technologies 10, 4(2000), 257–290.

[5]

Brhmie Balaram, Tony Greenham, and Jasmine Leonard. 2018. Artificial Intelligence: real public engagement. London: RSA. https://www. thersa. org/discover/publications-and-articles/reports/artificial-intelligence-realpublic-engagement(2018).

[6]

Imon Banerjee, Ananth Reddy Bhimireddy, John L Burns, Leo Anthony Celi, Li-Ching Chen, Ramon Correa, Natalie Dullerud, Marzyeh Ghassemi, Shih-Cheng Huang, Po-Chih Kuo, 2021. Reading Race: AI Recognises Patient’s Racial Identity In Medical Images. arXiv preprint arXiv:2107.10356(2021).

[7]

Darin Barney, Gabriella Coleman, Christine Ross, Jonathan Sterne, and Tamar Tembeck. 2016. The participatory condition in the digital age. Vol. 51. U of Minnesota Press.

[8]

Ruha Benjamin. 2019. Assessing risk, automating racism. Science 366, 6464 (2019), 421–422.

[9]

Lyria Bennett Moses and Janet Chan. 2018. Algorithmic prediction in policing: assumptions, evaluation, and accountability. Policing and society 28, 7 (2018), 806–822.

[10]

Aleks Berditchevskaia, Eirini Malliaraki, and Kathy Peach. 2020. Participatory AI for humanitarian innovation. (2020).

[11]

Abeba Birhane. 2021. Algorithmic injustice: a relational ethics approach. Patterns 2, 2 (2021), 100205.

[12]

Elizabeth Bondi, Lily Xu, Diana Acosta-Navas, and Jackson A Killian. 2021. Envisioning Communities: A Participatory Approach Towards AI for Social Good. arXiv preprint arXiv:2105.01774(2021).

[13]

Yves Cabannes. 2004. Participatory budgeting: a significant contribution to participatory democracy. Environment and urbanization 16, 1 (2004), 27–46.

[14]

Robert Chambers. 1994. The origins and practice of participatory rural appraisal. World development 22, 7 (1994), 953–969.

[15]

Alan Chan, Chinasa T Okolo, Zachary Terner, and Angelina Wang. 2021. The Limits of Global Inclusion in AI Development. arXiv preprint arXiv:2102.01265(2021).

[16]

Jason Chilvers and Matthew Kearnes. 2015. Remaking participation: Science, environment and emergent publics. Routledge.

[17]

Bill Cooke and Uma Kothari. 2001. Participation: The new tyranny?Zed books.

[18]

Sasha Costanza-Chock. 2020. Design justice: Community-led practices to build the worlds we need.

[19]

Nick Couldry and Ulises A Mejias. 2019. The costs of connection. Stanford University Press.

[20]

Nick Couldry and Ulises Ali Mejias. 2021. The decolonial turn in data and technology research: what is at stake and where is it heading?Information, Communication & Society(2021), 1–17.

[21]

Andy Dearden and Haider Rizvi. 2008. Participatory design and participatory development: a comparative review. (2008).

[22]

Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei. 2009. Imagenet: A large-scale hierarchical image database. In 2009 IEEE conference on computer vision and pattern recognition. Ieee, 248–255.

[23]

Emily Denton, Alex Hanna, Razvan Amironesei, Andrew Smart, and Hilary Nicole. 2021. On the genealogy of machine learning datasets: A critical history of ImageNet. Big Data & Society 8, 2 (2021), 20539517211035955.

[24]

Emily Denton, Alex Hanna, Razvan Amironesei, Andrew Smart, Hilary Nicole, and Morgan Klaus Scheuerman. 2020. Bringing the people back in: Contesting benchmark machine learning datasets. arXiv preprint arXiv:2007.07399(2020).

[25]

Joseph Donia and James A Shaw. 2021. Co-design and ethical artificial intelligence for health: An agenda for critical research and practice. Big Data & Society 8, 2 (2021), 20539517211065248.

[26]

Pelle Ehn and Morten Kyng. 1987. The collective resource approach to systems design. Computers and democracy(1987), 17–57.

[27]

Paul Farmer, Fernet Léandre, Joia Mukherjee, Rajesh Gupta, Laura Tarter, and Jim Yong Kim. 2001. Community-based treatment of advanced HIV disease: introducing DOT-HAART (directly observed therapy with highly active antiretroviral therapy).Bulletin of the World Health Organization 79, 12 (2001), 1145.

[28]

James Ferguson. 1994. The anti-politics machine:” development,” depoliticization, and bureaucratic power in Lesotho. U of Minnesota Press.

[29]

Paolo Freire. 1996. Pedagogy of the oppressed (revised). New York: Continuum (1996).

[30]

Seth Frey, PM Krafft, and Brian C Keegan. 2019. ” This Place Does What It Was Built For” Designing Digital Institutions for Participatory Change. Proceedings of the ACM on Human-Computer Interaction 3, CSCW(2019), 1–31.

[31]

Iason Gabriel. 2017. Effective altruism and its critics. Journal of Applied Philosophy 34, 4 (2017), 457–473.

[32]

Iason Gabriel. 2022. Toward a Theory of Justice for Artificial Intelligence. Daedalus 151, 2 (2022), 218–231.

[33]

Timnit Gebru, Jamie Morgenstern, Briana Vecchione, Jennifer Wortman Vaughan, Hanna Wallach, Hal Daumé Iii, and Kate Crawford. 2021. Datasheets for datasets. Commun. ACM 64, 12 (2021), 86–92.

Digital Library

[34]

R Stuart Geiger, Kevin Yu, Yanlai Yang, Mindy Dai, Jie Qiu, Rebekah Tang, and Jenny Huang. 2020. Garbage in, garbage out? Do machine learning application papers in social computing report where human-labeled training data comes from?. In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency. 325–336.

Digital Library

[35]

Tim Graham. 2021. Māori are trying to save their language from Big Tech. https://www.wired.co.uk/article/maori-language-tech

[36]

Mary L Gray and Siddharth Suri. 2019. Ghost work: How to stop Silicon Valley from building a new global underclass. Eamon Dolan Books.

[37]

Christopher Groves. 2017. Remaking participation: Science, environment and emergent publics.

[38]

Aaron Halfaker and R Stuart Geiger. 2020. Ores: Lowering barriers with participatory machine learning in wikipedia. Proceedings of the ACM on Human-Computer Interaction 4, CSCW2(2020), 1–37.

Digital Library

[39]

Christina N Harrington. 2020. The forgotten margins: what is community-based participatory health design telling us?Interactions 27, 3 (2020), 24–29.

Digital Library

[40]

Sarah Holland, Ahmed Hosny, Sarah Newman, Joshua Joseph, and Kasia Chmielinski. 2018. The dataset nutrition label: A framework to drive higher data quality standards. arXiv preprint arXiv:1805.03677(2018).

[41]

Ben Hutchinson, Andrew Smart, Alex Hanna, Emily Denton, Christina Greer, Oddur Kjartansson, Parker Barnes, and Margaret Mitchell. 2021. Towards accountability for machine learning datasets: Practices from software engineering and infrastructure. In Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency. 560–575.

Digital Library

[42]

Lilly C Irani and M Six Silberman. 2013. Turkopticon: Interrupting worker invisibility in amazon mechanical turk. In Proceedings of the SIGCHI conference on human factors in computing systems. 611–620.

Digital Library

[43]

Eun Seo Jo and Timnit Gebru. 2020. Lessons from archives: Strategies for collecting sociocultural data in machine learning. In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency. 306–316.

Digital Library

[44]

Michael Katell, Meg Young, Dharma Dailey, Bernease Herman, Vivian Guetler, Aaron Tam, Corinne Bintz, Daniella Raz, and P. M. Krafft. 2020. Toward Situated Interventions for Algorithmic Equity: Lessons from the Field. In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency(Barcelona, Spain) (FAT* ’20). Association for Computing Machinery, New York, NY, USA, 45–55.

Digital Library

[45]

Christopher M Kelty. 2017. The Participatory Development Toolkit. In Little Development Devices / Humanitarian Goods, Vol. 9. Limn.

[46]

Christopher M Kelty. 2020. The participant: A century of participation in four stories. University of Chicago Press.

[47]

Philip Kraft and Jørgen P Bansler. 1994. The collective resource approach: the Scandinavian experience. Scandinavian Journal of Information Systems 6, 1 (1994), 4.

Digital Library

[48]

Yann LeCun, Yoshua Bengio, and Geoffrey Hinton. 2015. Deep learning. nature 521, 7553 (2015), 436–444.

[49]

Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, 2019. WeBuildAI: Participatory framework for algorithmic governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW(2019), 1–35.

Digital Library

[50]

Min Kyung Lee, Ishan Nigam, Angie Zhang, Joel Afriyie, Zhizhen Qin, and Sicun Gao. [n.d.]. Participatory Algorithmic Management for Worker Well-Being. ([n. d.]).

[51]

Lord Frederick JD Lugard. 1922. The dual mandate in British tropical Africa. Routledge.

[52]

Kristian Lum and William Isaac. 2016. To predict and serve?Significance 13, 5 (2016), 14–19.

[53]

John Mackenzie, Poh-Ling Tan, Suzanne Hoverman, and Claudia Baldwin. 2012. The value and limitations of participatory action research methodology. Journal of hydrology 474(2012), 11–21.

[54]

Michael Majale. 2008. Employment creation through participatory urban planning and slum upgrading: The case of Kitale, Kenya. Habitat International 32, 2 (2008), 270–282.

[55]

Ghazala Mansuri and Vijayendra Rao. 2012. Localizing development: Does participation work?(2012).

[56]

Donald Martin Jr, Vinodkumar Prabhakaran, Jill Kuhlberg, Andrew Smart, and William S Isaac. 2020. Participatory problem formulation for fairer machine learning through community based system dynamics. arXiv preprint arXiv:2005.07572(2020).

[57]

Sabelo Mhlambi. 2020. From rationality to relationality: ubuntu as an ethical and human rights framework for artificial intelligence governance. Carr Center for Human Rights Policy Discussion Paper Series 9 (2020).

[58]

Margaret Mitchell, Simone Wu, Andrew Zaldivar, Parker Barnes, Lucy Vasserman, Ben Hutchinson, Elena Spitzer, Inioluwa Deborah Raji, and Timnit Gebru. 2019. Model cards for model reporting. In Proceedings of the conference on fairness, accountability, and transparency. 220–229.

Digital Library

[59]

Timothy Mitchell. 2002. Rule of experts. University of California Press.

[60]

Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial theory as sociotechnical foresight in artificial intelligence. Philosophy & Technology 33, 4 (2020), 659–684.

[61]

Daniel P Moynihan. 1969. Maximum Feasible Misunderstanding; Community Action in the War on Poverty.(1969).

[62]

Michael J Muller and Allison Druin. 2012. Participatory design: The third space in human–computer interaction. In The Human–Computer Interaction Handbook. CRC Press, 1125–1153.

[63]

Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Tajudeen Kolawole, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Hassan Muhammad, Salomon Kabongo, Salomey Osei, 2020. Participatory research for low-resourced machine translation: A case study in african languages. arXiv preprint arXiv:2010.02353(2020).

[64]

Jennifer Pierre, Roderic Crooks, Morgan Currie, Britt Paris, and Irene Pasquetto. 2021. Getting Ourselves Together: Data-centered participatory design research & epistemic burden. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems. 1–11.

Digital Library

[65]

Kathryn S Quick and Martha S Feldman. 2011. Distinguishing participation and inclusion. Journal of planning education and research 31, 3 (2011), 272–290.

[66]

Manish Raghavan, Solon Barocas, Jon Kleinberg, and Karen Levy. 2020. Mitigating bias in algorithmic hiring: Evaluating claims and practices. In Proceedings of the 2020 conference on fairness, accountability, and transparency. 469–481.

Digital Library

[67]

Stephanie Carroll Rainie, Tahu Kukutai, Maggie Walter, Oscar Luis Figueroa-Rodríguez, Jennifer Walker, and Per Axelsson. 2019. Indigenous data sovereignty. (2019).

[68]

Rashida Richardson, Jason M Schultz, and Kate Crawford. 2019. Dirty data, bad predictions: How civil rights violations impact police data, predictive policing systems, and justice. NYUL Rev. Online 94(2019), 15.

[69]

Sarah T Roberts. 2019. Behind the screen. In Behind the Screen. Yale University Press.

[70]

Nithya Sambasivan, Shivani Kapania, Hannah Highfill, Diana Akrong, Praveen Paritosh, and Lora M Aroyo. 2021. “Everyone wants to do the model work, not the data work”: Data Cascades in High-Stakes AI. In proceedings of the 2021 CHI Conference on Human Factors in Computing Systems. 1–15.

Digital Library

[71]

Scott Scheall and Parker Crutchfield. 2021. The priority of the epistemic. Episteme 18, 4 (2021), 726–737.

[72]

Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and abstraction in sociotechnical systems. In Proceedings of the conference on fairness, accountability, and transparency. 59–68.

Digital Library

[73]

Amartya Kumar Sen. 2009. The idea of justice. Harvard University Press.

[74]

Mark P Sendak, William Ratliff, Dina Sarro, Elizabeth Alderton, Joseph Futoma, Michael Gao, Marshall Nichols, Mike Revoir, Faraz Yashar, Corinne Miller, 2020. Real-world integration of a sepsis deep learning technology into routine clinical care: implementation study. JMIR medical informatics 8, 7 (2020), e15182.

[75]

Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2020. Participation is not a design fix for machine learning. arXiv preprint arXiv:2007.02423(2020).

[76]

Gayatri Chakravorty Spivak. 2003. Can the subaltern speak?Die Philosophin 14, 27 (2003), 42–58.

[77]

Kentaro Toyama. 2015. Geek heresy: Rescuing social change from the cult of technology. PublicAffairs.

[78]

Sabine N van der Veer, Lisa Riste, Sudeh Cheraghi-Sohi, Denham L Phipps, Mary P Tully, Kyle Bozentko, Sarah Atwood, Alex Hubbard, Carl Wiper, Malcolm Oswald, 2021. Trading off accuracy and explainability in AI decision-making: findings from 2 citizens’ juries. Journal of the American Medical Informatics Association 28, 10(2021), 2128–2138.

[79]

Maja Van der Velden, Christina Mörtberg, 2015. Participatory design and design for values. Handbook of Ethics, Values, and Technological Design: Sources, Theory, Values and Application Domains(2015), 41–66.

[80]

Carissa Véliz. 2020. Privacy is power. Random House Australia.

[81]

Jenny Waycott, Frank Vetere, Sonja Pedell, Amee Morgans, Elizabeth Ozanne, and Lars Kulik. 2016. Not for me: Older adults choosing not to participate in a social isolation intervention. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems. 745–757.

Digital Library

[82]

Susanne Weber, Marian Harbach, and Matthew Smith. 2015. Participatory design for security-related user interfaces. Proc. USEC 15(2015).

[83]

Shoshana Zuboff. 2019. The age of surveillance capitalism: The fight for a human future at the new frontier of power. Profile books.

Cited By

Miller TDurlik IŁobodzińska ADorobczyński LJasionowski R(2024)AI in Context: Harnessing Domain Knowledge for Smarter Machine LearningApplied Sciences10.3390/app14241161214:24(11612)Online publication date: 12-Dec-2024
https://doi.org/10.3390/app142411612
Jaiswal AShah AHarjadi CWindgassen EWashington P(2024)Ethics of the Use of Social Media as Training Data for Artificial Intelligence Models used for Digital Phenotyping: Commentary (Preprint)JMIR Formative Research10.2196/59794Online publication date: 22-Apr-2024
https://doi.org/10.2196/59794
Nankya HAlibu VMatovu EWamala EBarugahare J(2024)Community engagement conduct for genetics and genomics research: a qualitative study of the experiences and perspectives of key stakeholders in UgandaBMC Medical Ethics10.1186/s12910-024-01137-625:1Online publication date: 27-Nov-2024
https://doi.org/10.1186/s12910-024-01137-6
Show More Cited By

Index Terms

Power to the People? Opportunities and Challenges for Participatory AI
1. Human-centered computing
  1. Interaction design
    1. Interaction design theory, concepts and paradigms

Recommendations

Power and Public Participation in AI
EAAMO '23: Proceedings of the 3rd ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization

The rapid growth of AI in contemporary life has outpaced the public participation necessary for society to determine how these technologies should be used. As scholars respond to this challenge by exploring new modes of public participation in AI, we ...
Participatory design through a cultural lens: insights from postcolonial theory
PDC '14: Proceedings of the 13th Participatory Design Conference: Short Papers, Industry Cases, Workshop Descriptions, Doctoral Consortium papers, and Keynote abstracts - Volume 2

This paper examines challenges faced in participatory design's confrontation with cultural complexity in contexts of intercultural encounter and transnational exchange. We argue that there is need for more elaborate approaches to culture, technology, ...
Participation, power, critique: constructing a standard for electronic patient records
PDC '06: Proceedings of the ninth conference on Participatory design: Expanding boundaries in design - Volume 1

This paper examines the scope of participatory design on the basis of the case of a national standard for electronic patient records (EPR) in Denmark. The relationship between participatory methods and techniques on the one hand and critical and ...

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences

EAAMO '22: Proceedings of the 2nd ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization

October 2022

239 pages

ISBN:9781450394772

DOI:10.1145/3551624

Copyright © 2022 Owner/Author.

This work is licensed under a Creative Commons Attribution International 4.0 License.

Sponsors

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 17 October 2022

Check for updates

Author Tags

Qualifiers

Research-article
Research
Refereed limited

Conference

EAAMO '22

Sponsor:

EAAMO '22: Equity and Access in Algorithms, Mechanisms, and Optimization

October 6 - 9, 2022

VA, Arlington, USA

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

80
Total Citations
View Citations
6,744
Total Downloads

Downloads (Last 12 months)4,031
Downloads (Last 6 weeks)551

Reflects downloads up to 24 Dec 2024

Other Metrics

View Author Metrics

Citations

Cited By

Miller TDurlik IŁobodzińska ADorobczyński LJasionowski R(2024)AI in Context: Harnessing Domain Knowledge for Smarter Machine LearningApplied Sciences10.3390/app14241161214:24(11612)Online publication date: 12-Dec-2024
https://doi.org/10.3390/app142411612
Jaiswal AShah AHarjadi CWindgassen EWashington P(2024)Ethics of the Use of Social Media as Training Data for Artificial Intelligence Models used for Digital Phenotyping: Commentary (Preprint)JMIR Formative Research10.2196/59794Online publication date: 22-Apr-2024
https://doi.org/10.2196/59794
Nankya HAlibu VMatovu EWamala EBarugahare J(2024)Community engagement conduct for genetics and genomics research: a qualitative study of the experiences and perspectives of key stakeholders in UgandaBMC Medical Ethics10.1186/s12910-024-01137-625:1Online publication date: 27-Nov-2024
https://doi.org/10.1186/s12910-024-01137-6
Gourlet PRicci DCrépel M(2024)Reclaiming artificial intelligence accounts: A plea for a participatory turn in artificial intelligence inquiriesBig Data & Society10.1177/2053951724124809311:2Online publication date: 6-May-2024
https://doi.org/10.1177/20539517241248093
Medrado AVerdegem P(2024)Participatory action research in critical data studies: Interrogating AI from a South–North approachBig Data & Society10.1177/2053951724123586911:1Online publication date: 18-Mar-2024
https://doi.org/10.1177/20539517241235869
Sloane M(2024)Controversies, contradiction, and “participation” in AIBig Data & Society10.1177/2053951724123586211:1Online publication date: 25-Feb-2024
https://doi.org/10.1177/20539517241235862
Gallegos IRossi RBarrow JTanjim MKim SDernoncourt FYu TZhang RAhmed N(2024)Bias and Fairness in Large Language Models: A SurveyComputational Linguistics10.1162/coli_a_0052450:3(1097-1179)Online publication date: 1-Sep-2024
https://doi.org/10.1162/coli_a_00524
Kallina ESingh J(2024)Stakeholder Involvement for Responsible AI Development: A Process FrameworkProceedings of the 4th ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization10.1145/3689904.3694698(1-14)Online publication date: 29-Oct-2024
https://dl.acm.org/doi/10.1145/3689904.3694698
Kong EHuang KGautam AFarzan RLópez CCardoso Llach DQuercia DMustafa MNiu SWong-Villacrés M(2024)Envisioning Possibilities and Challenges of AI for Personalized Cancer CareCompanion Publication of the 2024 Conference on Computer-Supported Cooperative Work and Social Computing10.1145/3678884.3681885(415-421)Online publication date: 11-Nov-2024
https://dl.acm.org/doi/10.1145/3678884.3681885
Fassbender JHenderson T(2024)Participatory to what end? Mapping motivations for participatory approaches in data-driven projectsProceedings of the 2024 International Conference on Information Technology for Social Good10.1145/3677525.3678675(301-305)Online publication date: 4-Sep-2024
https://dl.acm.org/doi/10.1145/3677525.3678675
Show More Cited By

View Options

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

Media

Figures

Other

Tables

View Table of Contents