Data Inequality $ = $ Income Inequality

Session Topic:Data Inequality / Income Inequality

Wednesday 2E

Convener: Kris Alman

Notes-taker(s): Kris Alman & Matt Berry

Discussion notes, key understandings, outstanding questions, observations, and, if appropriate to this discussion: action items, next steps:

Income inequality/ Data inequality

If data is concentrated in fewer hands, will income inequality grow? And will this further tilt power structures? Can we measure data inequality, like Gini coefficient does to measure income inequality?

21st century post-industrial economy called knowledge or information economy. Influence on education: STEM careers (STEAM acknowledges art—creativity/innovation—as important.) Compared to industrial revolution where people were stripped of land and were unaware what happened & how livelihoods changed. Will middle class “knowledge workers” (doctors, teachers, IT, musicians, etc.) become devalued as data is gleaned and monetized by big corporations?

“Privacy is a nonrenewable resource. Once it gets consumed, it is gone.” Frank McSherry of Microsoft Research Silicon Valley in Mountain View, Calif. http://www.simonsfoundation.org/quanta/20121210-privacy-by-the-numbers-a-new-approach-to-safeguarding-data/ http://www.scientificamerican.com/article/privacy-by-the-numbers-a-new-approach-to-safeguarding-data/

Controversial concept. With each birth, privacy is a renewable resource!

Pandora’s Box is open and data collected without our ability to opt-in or out.

• Decentralization with Peer to Peer connections important.
• Demand education and transparency of data collected by both business & government. We should not have different standards for government and private sector as they have merged.
• Consentualized data can occur through:
  • Anonymous transactions (using public/private keys)
  • Privacy by design

Transparency is limited by bad laws. E.g. transparency of prices in health care and trade secret laws that prevent disclosure of negotiated rates for services.

There is a difference between explicit and inferred data. Marketing surveillance comes from explicit info shared on sites like facebook.

Example of inferred data. Defense Intelligence Agency took photographs of and analyzed protests with Topsy. Determined that adding food carts decreased violence. http://topsy.com/

Predictive analytics with data collected over which we have no control (or know exists) is concerning.

Trade agreements like TPP and TTIP impact data inequality (such as who controls data for international companies; how might net neutrality be impacted). Secret trade agreements (corporations writing them) are writing them without transparency to public. Could this impact net neutrality or data ownership/access? How does this impact governance? Acknowledgement that we are an oligarchy. Recent Huff Post article that demonstrates 83% of legislation is contrary to public opinion.

Good resource:

Knowledge Ecology International, Attending and mending the knowledge ecosystem (KEI): http://keionline.org/about

“a not for profit non governmental organization that searches for better outcomes, including new solutions, to the management of knowledge resources. KEI is focused on social justice, particularly for the most vulnerable populations, including low-income persons and marginalized groups. There are probably 5 billion people who live in the margins of the global economy, and an entire planet that depends upon knowledge for economic and personal development, education and health, political power and freedom, culture and fun.”

Joseph Stiglitz, economist and a professor at Columbia University, is an advisor. He won Nobel Prize in Economics for his analyses of markets with asymmetric information.http://keionline.org/node/18

Recommended book: Who Owns the Future?http://www.amazon.com/Who-Owns-Future-Jaron-Lanier/dp/1451654960