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Claudia Abreu Lopes Digital Health Week - 21 August 2019 Big Data for SDG3 and SDG5 Promise and inequality traps #SDG5forHealth #Equality4Health #SDG3forSDG5

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Page 1: Big Data for SDG3 and SDG5 Promise and inequality traps · 2019-09-10 · Big Data for SDG3 and SDG5 Promise and inequality traps #SDG5forHealth #Equality4Health #SDG3forSDG5

Claudia Abreu Lopes

Digital Health Week - 21 August 2019

Big Data for SDG3 and SDG5Promise and inequality traps

#SDG5forHealth #Equality4Health #SDG3forSDG5

Page 2: Big Data for SDG3 and SDG5 Promise and inequality traps · 2019-09-10 · Big Data for SDG3 and SDG5 Promise and inequality traps #SDG5forHealth #Equality4Health #SDG3forSDG5
Page 3: Big Data for SDG3 and SDG5 Promise and inequality traps · 2019-09-10 · Big Data for SDG3 and SDG5 Promise and inequality traps #SDG5forHealth #Equality4Health #SDG3forSDG5

2019 SDG Gender Index

Page 4: Big Data for SDG3 and SDG5 Promise and inequality traps · 2019-09-10 · Big Data for SDG3 and SDG5 Promise and inequality traps #SDG5forHealth #Equality4Health #SDG3forSDG5

Of the 14 indicators for SDG5, only 4 indicators

have internationally accepted standards and data is regularly

collected by most countries

Of the 51 gender-related indicators

across 14 SDGs, only one quarter have

gender data available

Page 5: Big Data for SDG3 and SDG5 Promise and inequality traps · 2019-09-10 · Big Data for SDG3 and SDG5 Promise and inequality traps #SDG5forHealth #Equality4Health #SDG3forSDG5
Page 6: Big Data for SDG3 and SDG5 Promise and inequality traps · 2019-09-10 · Big Data for SDG3 and SDG5 Promise and inequality traps #SDG5forHealth #Equality4Health #SDG3forSDG5

Accelerating progress: An empowered, inclusive and equal Asia and the Pacific. UN, Asian Development Bank and UNDP 2019 .

Page 7: Big Data for SDG3 and SDG5 Promise and inequality traps · 2019-09-10 · Big Data for SDG3 and SDG5 Promise and inequality traps #SDG5forHealth #Equality4Health #SDG3forSDG5

Accelerating progress: An empowered, inclusive and equal Asia and the Pacific. UN, Asian Development Bank and UNDP 2019 .

Page 8: Big Data for SDG3 and SDG5 Promise and inequality traps · 2019-09-10 · Big Data for SDG3 and SDG5 Promise and inequality traps #SDG5forHealth #Equality4Health #SDG3forSDG5

• Volume [data exhaust]

• Variety [messy, multi-format data]

• Velocity [real-time data]

• Vinculation [data linkages]

• Veracity [measurement and interpretation]

Big Data

Page 9: Big Data for SDG3 and SDG5 Promise and inequality traps · 2019-09-10 · Big Data for SDG3 and SDG5 Promise and inequality traps #SDG5forHealth #Equality4Health #SDG3forSDG5
Page 10: Big Data for SDG3 and SDG5 Promise and inequality traps · 2019-09-10 · Big Data for SDG3 and SDG5 Promise and inequality traps #SDG5forHealth #Equality4Health #SDG3forSDG5

• Human sourced data

• Process mediated data

• Machine generated data

• Media sourced data

Page 11: Big Data for SDG3 and SDG5 Promise and inequality traps · 2019-09-10 · Big Data for SDG3 and SDG5 Promise and inequality traps #SDG5forHealth #Equality4Health #SDG3forSDG5
Page 12: Big Data for SDG3 and SDG5 Promise and inequality traps · 2019-09-10 · Big Data for SDG3 and SDG5 Promise and inequality traps #SDG5forHealth #Equality4Health #SDG3forSDG5

Using Twitter data to monitor trends in VAW in Brazil

Page 13: Big Data for SDG3 and SDG5 Promise and inequality traps · 2019-09-10 · Big Data for SDG3 and SDG5 Promise and inequality traps #SDG5forHealth #Equality4Health #SDG3forSDG5

Monitoring disease outbreak in Uganda

https://diseaseoutbreaks.unglobalpulse.net//uganda/

Page 14: Big Data for SDG3 and SDG5 Promise and inequality traps · 2019-09-10 · Big Data for SDG3 and SDG5 Promise and inequality traps #SDG5forHealth #Equality4Health #SDG3forSDG5

Expanding health coverage in Malawi using mobile phone data

https://coopersmith.org/blog/2019/4/17/expanding-health-coverage-using-mobile-phone-data

Page 15: Big Data for SDG3 and SDG5 Promise and inequality traps · 2019-09-10 · Big Data for SDG3 and SDG5 Promise and inequality traps #SDG5forHealth #Equality4Health #SDG3forSDG5

Turning radio conversations into data in Uganda

https://unfoundation.org/blog/post/when-old-technology-meets-new-how-un-global-pulse-is-using-radio-and-ai-to-leave-no-voice-behind/

Page 16: Big Data for SDG3 and SDG5 Promise and inequality traps · 2019-09-10 · Big Data for SDG3 and SDG5 Promise and inequality traps #SDG5forHealth #Equality4Health #SDG3forSDG5
Page 17: Big Data for SDG3 and SDG5 Promise and inequality traps · 2019-09-10 · Big Data for SDG3 and SDG5 Promise and inequality traps #SDG5forHealth #Equality4Health #SDG3forSDG5

Ethical and privacy issues

Page 18: Big Data for SDG3 and SDG5 Promise and inequality traps · 2019-09-10 · Big Data for SDG3 and SDG5 Promise and inequality traps #SDG5forHealth #Equality4Health #SDG3forSDG5

Risks, harms and benefits tool

Page 19: Big Data for SDG3 and SDG5 Promise and inequality traps · 2019-09-10 · Big Data for SDG3 and SDG5 Promise and inequality traps #SDG5forHealth #Equality4Health #SDG3forSDG5

Characteristics of Big Data

▪ Big (rare events, heterogeneity, small differences) ▪ Always-on▪ Nonreactive ▪ Incomplete

▪ Inaccessible▪ Non-representative▪ Drifting▪ Algorithmically confused▪ Dirty▪ Sensitive

BUT …

Page 20: Big Data for SDG3 and SDG5 Promise and inequality traps · 2019-09-10 · Big Data for SDG3 and SDG5 Promise and inequality traps #SDG5forHealth #Equality4Health #SDG3forSDG5

Risks and challenges

• Elite capture: major risk of ‘black holes’ of data where entire demographics can be missed

because of restricted access and use

• Restricted use: factors that constrain women’s ability to participate in social media or

other interactive platforms

• Ambient sexism: perceived misogyny on social media

• Platform drifts: population, usage and system

• Ethical and privacy issues

Page 21: Big Data for SDG3 and SDG5 Promise and inequality traps · 2019-09-10 · Big Data for SDG3 and SDG5 Promise and inequality traps #SDG5forHealth #Equality4Health #SDG3forSDG5

South Asia has the world’s largest mobile gender gap

In India, 67% of men own mobile phones, but only 33% percent of women do.

South Asian countries in general are clear outliers among countries of similar levels of development, with India, Pakistan, and Bangladesh exhibiting some of the world’s highest gender gaps in access to technology

Page 22: Big Data for SDG3 and SDG5 Promise and inequality traps · 2019-09-10 · Big Data for SDG3 and SDG5 Promise and inequality traps #SDG5forHealth #Equality4Health #SDG3forSDG5

Economic barriers

Barboni et al. (2018). A Tough Call: Understanding barriers to and impacts of women’s mobile phone adoption in India. Harvard Kennedy School.

Page 23: Big Data for SDG3 and SDG5 Promise and inequality traps · 2019-09-10 · Big Data for SDG3 and SDG5 Promise and inequality traps #SDG5forHealth #Equality4Health #SDG3forSDG5

Normative barriers

Barboni et al. (2018). A Tough Call: Understanding barriers to and impacts of women’s mobile phone adoption in India. Harvard Kennedy School.

Page 24: Big Data for SDG3 and SDG5 Promise and inequality traps · 2019-09-10 · Big Data for SDG3 and SDG5 Promise and inequality traps #SDG5forHealth #Equality4Health #SDG3forSDG5

Real girls, real lives, connected – A global study of girls’ access and usage of mobile, told through 3000 voices. Girl Effect and Vodafone Foundation (2018)

Page 25: Big Data for SDG3 and SDG5 Promise and inequality traps · 2019-09-10 · Big Data for SDG3 and SDG5 Promise and inequality traps #SDG5forHealth #Equality4Health #SDG3forSDG5

Real girls, real lives, connected – A global study of girls’ access and usage of mobile, told through 3000 voices. Girl Effect and Vodafone Foundation (2018)

Reasons for not owning a phone

Page 26: Big Data for SDG3 and SDG5 Promise and inequality traps · 2019-09-10 · Big Data for SDG3 and SDG5 Promise and inequality traps #SDG5forHealth #Equality4Health #SDG3forSDG5

Big Data and Artificial Intelligence

Page 27: Big Data for SDG3 and SDG5 Promise and inequality traps · 2019-09-10 · Big Data for SDG3 and SDG5 Promise and inequality traps #SDG5forHealth #Equality4Health #SDG3forSDG5

Delloite (2018). Privacy is

Paramount | Personal Data

Protection in Africa Personal

Data Protection in Africa

Page 28: Big Data for SDG3 and SDG5 Promise and inequality traps · 2019-09-10 · Big Data for SDG3 and SDG5 Promise and inequality traps #SDG5forHealth #Equality4Health #SDG3forSDG5

Citizen-generated data (CGD) is data that people or their organisations

produce to directly monitor, demand or drive change on issues that affect

them.

It is actively given by citizens, providing direct representations of their

perspectives and an alternative to datasets collected by governments or

international institutions (Civicus, 2014).

Expanding the room…

Page 29: Big Data for SDG3 and SDG5 Promise and inequality traps · 2019-09-10 · Big Data for SDG3 and SDG5 Promise and inequality traps #SDG5forHealth #Equality4Health #SDG3forSDG5

Supplement big data with CGD

- To improve issues of representation and coverage

- Particularly for hard to reach populations, ensuring that NoLB

- To validate trends and insights generated by Big Data

- To involve citizens in the production, interpretation and use of data

Page 30: Big Data for SDG3 and SDG5 Promise and inequality traps · 2019-09-10 · Big Data for SDG3 and SDG5 Promise and inequality traps #SDG5forHealth #Equality4Health #SDG3forSDG5
Page 31: Big Data for SDG3 and SDG5 Promise and inequality traps · 2019-09-10 · Big Data for SDG3 and SDG5 Promise and inequality traps #SDG5forHealth #Equality4Health #SDG3forSDG5

Thank you!@cabreulopes

Page 32: Big Data for SDG3 and SDG5 Promise and inequality traps · 2019-09-10 · Big Data for SDG3 and SDG5 Promise and inequality traps #SDG5forHealth #Equality4Health #SDG3forSDG5

Claudia Abreu Lopes

Digital Health Week - 21 August 2019

Big Data for SDG3 and SDG5Promise and inequality traps

#SDG5forHealth #Equality4Health #SDG3forSDG5