A reformation of digital and democracy literacy led by civil society

Once upon a time, the codes that guided society were the province of a few. The word of God was read and interpreted by priests and men of the church who told the people what the book said, what the codes for a good life were. And the people did as they were told.

Then more people learned to read, printing technology changed, and still more people learned to read. Violations of power from those who had controlled the code were exposed, and religious reformation was called for. New technologies and more public interrogation of the "code" began and many took over what had the been the tightly-held purview of a few.

(The above is a deliberately oversimplified analysis of 15-18th century western European historical canon, minus all the power struggles, racism, sexism, extra-Christian turmoil, and colonialism. I'm trying to make a point.)

Once upon a time, software code drove devices used mostly by those who could read and write software code. Then these devices and the networks they powered were opened to most (not quite all). And all became dependent on software powered gadgetry and digital networks. But the code remained the province of a few, even as some led movements for opens source, open data, open algorithms, open governance. But, still the many had no understanding of the nature of the code, its limitations or bounds.

As this code and its disciples brought their tools, which were designed around the efficiency of market forces, into other realms of life, such as the household, political systems, and civil society there was tension. The value of efficiency, coded into the software, didn't always fit smoothly with the values of the household (privacy) or that of the governing systems (participation and representation) or civil society (justice, equity, beauty).

And so there was a clash of values, a clash of codes. And the priests of software code and the priests of governance found themselves at odds. And the people - to whom open data was given - were not equipped to use it.

And some of the nonprofits and foundations and associations that constitute civil society interrogated some of the software code. Over and over again they pointed out ways in which the code was misaligned with the task to which it was being applied. Examples of racial discrimination. Of algorithmic bias. Of new divides and new versions of exclusionary practice. Civil society served one of its most important functions - checking and re-checking the power of governments and markets (and their digital tools).

Some of the answer lay in applying existing democratic process technologies - such as due process - to applications of algorithmic decision making. And this was good.

Still, a more fundamental structural divide remained. Call it a linguistic divide. Between those  "fluent" in digital and those "fluent" in democracy and civil society. A reformation in access and capacity and understanding was needed.

And this is where we are today. 

Codes - software and legal - are sets of values. Written and enforced. When using digital technologies within democratic systems or for democratic purposes the values embodied in the codes need to align. They need to be able to interrogate each other and for the people to understand what is meant, what is captured in the code, what is being promoted or enforced by the collective set of rules and tools.

The common term for helping individuals, non techies, understand digital data and systems, codes and algorithms, is data literacy. This is not my favorite term, but let's use it for now, recognizing that it its not a one way street. People need to better understand how digital systems and codes work and software coders need to the priorities and principles of of democratic practice - both "literacies" are needed.

All involved, not just the priests with the books (not just the software coders) but the people, our agents, our elected officials, our judges) need to be able to understand the code.

Algorithmic accountability, open data, machine learning must be designed by and with those who understand the principles of democratic governance. It is the job of those who understand these systems to teach those who understand algorithms and vice versa. 

In other words, digital technologists and tacticians must teach and learn from democratic theorists and tacticians.  All who are citizens, all in civil society, all in public agencies - these are the democracy tacticians I'm talking about.

We need both codes - the codes of democracy and software code - to be written, used, held accountable, and procedurally applied and interrogated together.

One does not have the solutions for the other, they must build solutions together. If for no other reason than we (in democratic societies at least) are all dependent on both democracy and software. There is no "they," we are we. 

Resources - Tech for Social Good

I just finished teaching a continuing studies class at Stanford on Tech for Social Good. My colleague and co-teacher, Rob Reich and I assembled this list of free online sites to follow/ newsletters to read for the class. I thought I'd share it here as well. Enjoy! (and let me know what I'm missing)

Civic Hall and Personal Democracy Forum (and First Post newsletter)

http://civichall.org/civicist

Data & Society Institute

http://www.datasociety.net/

Equal Future – Social Justice and Technology

https://www.equalfuture.us/

Knight Foundation Tech for Civic Engagement

http://www.knightfoundation.org/funding-initiatives/tech-engagement/

Markets For Good
http://www.marketsforgood.org

NYU Gov Lab  - Friday newsletter
http://www.thegovlab.org/

Social Good

http://mashable.com/category/social-good/

Stanford Cyber Initiative Blog ( great weekly newsletter)

https://cyber.stanford.edu/news/cyber-social-systems-blog

Stanford PACS

http://pacscenter.stanford.edu/

Stanford PACS Digital Civil Society Lab

http://pacscenter.stanford.edu/digital-civil-society/

Stanford Social Innovation Review – Technology

http://ssir.org/topics/category/technology

TechCrunch

http://techcrunch.com/

UW Tech Policy Lab

http://techpolicylab.org/

Newsletters I read/Medium sites I follow(ish)

Jack Smith - Circuit Breaker

Deb Chacra’s MetaFoundry

Melody Kramer’s Mel’s Sandbox

David Pell’s NextDraft

Brian Walsh All Things Impact

Greenpeace's MobLab Dispatch

Cathy O’Neil Mathbabe

https://medium.com/@backchannel

What is it about the nonprofit structure?

You’ve probably heard about OpenAI — a new, billion dollar nonprofit to focus on artificial intelligence research that is good for humanity. In their own words:

“OpenAI is a non-profit artificial intelligence research company. Our goal is to advance digital intelligence in the way that is most likely to benefit humanity as a whole, unconstrained by a need to generate financial return.

Since our research is free from financial obligations, we can better focus on a positive human impact. We believe AI should be an extension of individual human wills and, in the spirit of liberty, as broadly and evenly distributed as possible.

The outcome of this venture is uncertain and the work is difficult, but we believe the goal and the structure are right. We hope this is what matters most to the best in the field.”

In an interview posted on the Singularity University newsletter, one of the founding researchers, Andrej Karpathy, a Stanford doctoral candidate who interned at Google and DeepMind, says:

“A lot of it comes from OpenAI as a non-profit. … It’s not clear that you would want a big for-profit company to have a huge lead, or even a monopoly over the research. It is primarily an issue of incentives, and the fact that they are not necessarily aligned with what is good for humanity. We are baking that into our DNA from the start.

Also, there are some benefits of being a non-profit that I didn’t really appreciate until now. People are actually reaching out and saying “we want to help”; …

OpenAI… encourages us to publish, to engage the public and academia, to Tweet, to blog. …. If something like [CRISPR which has great potential for benefiting — and hurting — humankind. Because of these ethical issues there was a recent conference on it in DC to discuss how we should go forward with it as a society] happens in AI during the course of OpenAI’s research — well, we’d have to talk about it. We are not obligated to share everything — in that sense the name of the company is a misnomer — but the spirit of the company is that we do by default.

In the end, if there is a small chance of something crazy happening in AI research, everything else being equal, do you want these advances to be made inside a commercial company, especially one that has monopoly on the research, or do you want this to happen within a non-profit?

We have this philosophy embedded in our DNA from the start that we are mindful of how AI develops, rather than just [a focus on] maximizing profit.

It’s a lot of responsibility. It’s a “lesser evil” argument; I think it’s still bad. But we’re not the only ones “controlling” the field — because of our open nature we welcome and encourage others to join in on the discussion. Also, what’s the alternative? In a way a non-profit, with sharing and safety in its DNA, is the best option for the field and the utility of the field.”

So here we have a case of knowledgeable people recognizing a threat and deciding that the way forward is to create a nonprofit organization. This moment has some historical precedent. In 1955, Albert Einstein, Bertrand Russell and several other scientists got together and issued a manifesto about the dangers of nuclear technologies. It would launch decades of Pugwash conferences and the anti-nuclear movement.

The founders of OpenAI also issued a manifesto. Back in January 2015, Stephen Hawking and Elon Musk, one of OpenAI’s key funders, signed an “Open Letter on Research Priorities for Robust and Beneficial Artificial Intelligence.” We’ve spent decades monitoring, signing treaties about, building and dismantling nuclear weapons. The Einstein-Russell Manifesto and Pugwash happened after the U.S. had detonated two atomic bombs and the world could agree on the horror they created. Nuclear capacity still plays a major role in global politics but efforts to prevent their use and spread have mostly succeeded. My questions are not about nuclear power or AI per se, they are about the viability of the nonprofit organization in today’s world of shifting public, private, and corporate roles.

• Will a set of voluntary manifestos and a few nonprofits work to keep AI from harming people? Unlike the nuclear weapons case, the likely builders of dangerous applications are not nation states, they are corporations. Unlike nuclear weapons (or energy) the component costs are dropping, not rising, and there is no singular component that can be tightly controlled (as in the case of enriched uranium).
• Is the strategy of “out R+D’ing” the commercial competitors via a nonprofit that will share some (most) of what it learns realistic? In most cases where there is competition between for-profits and nonprofits the capital scheme favors the commercial players (see, for example, car sharing. medical devices, pharmaceuticals)
• Is the governance model of nonprofits — no shareholders, public purpose mission, excess holdings limitations, nondistribution clauses — enough to direct research with potentially harmful applications away from those harms?

There will need to be other strategies to “control” dangerous AI. But the application of the U.S. nonprofit corporate model to a global challenge such as this provides a great moment to ask ourselves”.

• What can the nonprofit enterprise form do and what cannot it not accomplish?
• What kind of structure can best manage intellectual, digital, and algorithmic resources for long-term public benefit?
• How might open source governance models augment the nonprofit enterprise form and where, if anywhere, do they conflict?

Unlike the machine learning experts who are joining OpenAI, I see no reason to assume that the nonprofit structure is sufficient to accomplish their goals. If the challenges of AI are as great as these minds seem to suggest, is the “lesser evil” OK? 

I commend them for directing their expertise toward beneficial uses of the technology. I also think it’s time to reconsider the institutional technology of the nonprofit corporation. We need institutions that can generate, direct and hold digital resources for long-term public benefit; I’m not sure the current nonprofit firm is the answer.

Ethical, safe, and effective digital data use in civil society

The Digital Civil Society Lab held workshop on ethical, safe and effective digital data use in civil society. A synthesis of the meeting and two DRAFT tools we developed are online here.

We welcome your feedback

Technology, democracy, civil society

Loved this quote from Nathan Schneider in an article on the "slow technology" movement:

"There is a habit in tech culture of saying that the latest app is “democratizing” whatever it happens to do. This is lovely, but best not to confuse it with actual democracy. Democracy is about participation with control, freedom with accountability, privacy with transparency. Tech companies tend to pick and choose from that list rather inventively."*

Finding this on the same day that Pew Research shows just how little trust we Americans have for our data in the hands of either government or companies, I can't help but say, "Right! And now is the time for civil society to offer alternatives for the safe, secure,  ethical, and effective uses of digital data!"

And I'm looking forward to reading Geek Heresy: Rescuing Social Change from the Cult of Technology, by Kentaro Toyama, Associate Professor at the University of Michigan.  Those of you in DC on June 4th might consider checking out the book at New America Foundation's OTI event.



*Nathan Schneider, "The Joy of Slow Computing," The New Republic, Accessed online May 20, 2015 at http://www.newrepublic.com/article/121832/pleasure-do-it-yourself-slow-computing

Institutional philanthropy goes digital (slowly)

I often write about emergent forms of philanthropy, enabled or accelerated by digital technology. And I spend a lot of time looking for ways that established philanthropic institutions are or could be using these tools. Here are two recent examples:

HIPGive
Hispanics in Philanthropy is an association of foundation executives committed to expanding Hispanic leadership and giving and an international funders' collaborative. After many years of grantmaking and technical assistance to small organizations it has turned to the crowdfunding space to push this work even further. It has partnered with the W.K. Kellogg Foundation, Western Union, and California Wellness Foundation to launch HIPGive, a crowdfunding platform that will encourage giving to educational efforts. If it taps into a tiny percentage of the remittance flows in and among Hispanic communities those funds would add up quickly.

Why does the world need another crowdfunding platform? For some communities it may seem there are too many crowdfunding options (white-middle class-iphone-case designers, for example). For others, such as individual donors in Latin America, crowdfunding tools may not be familiar or trusted. HIPGive is about the networks, relationships and skills that it takes for a small organization or group of individuals to run a successful crowdfunding campaign. HIP is providing technical assistance on everything from marketing to matching grants. This is a great example of weaving together informal and formal giving, institutions like foundations with individuals and families of givers. It may also help claim all the many definitions and personas of philanthropists. The current site is being optimized for mobile use - as with any technology project it's constantly in process.

NewMusic USA
NewMusic USA is a grant making organization that supports the creation of new music. The organization resulted from the merger of two older organizations. When the new entity was formed it had the opportunity to design its grantmaking process from scratch. Kevin Clark and other members of the staff  turned to Kickstarter for inspiration, looking for ways that the application and reporting process could be useful to grantees rather than laborious and uncertain. The result? A participatory grants process that involves community advisors. A reporting process that uses the marketing of that grantees do of their concerts as the reporting for the grant. Yes, you read that right - the outreach activities of the grant and the grant reporting are one and the same. NewMusic provides an online system that lets grantees host web pages, concert announcements, do outreach via social media and count all that attention that gets generated via these systems as their grantee reporting! Imagine that, a grants reporting system that is actually helpful to the grantee. Who woulda thunk?

NewMusicUSA recognized that it could reinvent grantmaking processes using current technologies and behaviors. Because the organization is itself part of the community it serves (musicians helping musicians) the staff knows how real the time demands are on these artists.  It designed the funding process to help with marketing and time demands, as well as money. It

Both of these are examples of Values Aligned Technology. HIPGive has designed into it's crowdfunding efforts the trust, linguistic, cultural, and design features needed to encourage its community to try the platform. Crowdfunding - it's not just for hipsters anymore! Similarly, NewMusic USA could knew enough to design reporting defaults that served the applicants in a positive way. In doing so, the defaults it set for it technology mirror (and have nudged along) the default values in the relationships between funders and grantees. 

Ethics, data, mission and revenue

I just finished a three part series on digital values and civil society. We'll have to call this post part 3.5.

As I did so, I was (slightly) relieved to see that the Chronicle of Philanthropy raised an ethical eyebrow at the growing practice of nonprofits' selling data and digital data rights in their link to this story from The Philadelphia Inquirer.*

This is a great example of the ethical conundrums facing nonprofits in the digital age. Gather and sell people's data? Nothing new in that business model - it's been working ridiculously well for social media giants and search companies for more than a decade now (works great for data brokers also).

• Why should or shouldn't nonprofits sell data from those they work with? 
• When should they do it? 
• Under what conditions? 
• Is there any nonprofit/mission-driven special privilege or pass or encouragement we want to endorse where this practice is involved? 
• If there are special conditions for nonprofits or mission-based businesses what are they and who's going to monitor adherence to those conditions? 
• And if there are not special conditions for nonprofit enterprises regarding their use of this resource, why are they nonprofits?

Please consider how the logic behind your answer regarding data for pharmaceutical research (as examined in the story) extend (or not) to other types of data, because it's more than physiological information that gets shared, it's also demographic, geographic, and other identifying information.

Some data may have real public value. Since many of us gladly (unknowingly? with reservations?) exchange our data for free 2-day shipping, the exchange of data for life-saving medical breakthrough may well be worth it? How can we value these exchanges? Make them more visible? And what spectrum of rights might we want regarding how we protect and how we share our data and for what purposes?

Got an answer to these questions for your nonprofit or your foundation? Great. If so, you are way ahead of the rest of the sector, which is still writing ethical codes that ignore the value and challenges of digital data.




*In the same issue the Chronicle is running an ongoing series of "he said, she saids" about "tech for good." It's not about how many drones, how many 3D printers, or who uses bitcoin - it's about purpose, respect, accountability, and with what limits and rights we pursue digital opportunities to achieve our missions. But at least the Chronicle stories engage different viewpoints about digital - instead of acting like it's not there.

Values Aligned Technology

I've been thinking a lot about values, society, and technological design. I'm trying to articulate what, when, and how the values that shape civil society should be expressed with and within technology. What I do know is that it's not just at the point of use. We need tools that default to the values we care about, not just those that serve the company that built the tool or the government that regulates its use. We can't continue to duct-tape our tech tools into our social sector work or political protest.

So far, most of what I've read about this, and the thinking I participated in at the Ethics of Data Conference, talks about ethical decision making across the data lifecycle. This is an important start. But it doesn't seem to start early enough in the tech/data development process. The values of the end user and the end uses need to be designed into the tools from the beginning.

(photo: https://wiki.responsibledata.io/Data_in_the_project_lifecycle)

Think about this. In civil society, for example, voluntary participation is not just a key value, it's a defining premise of the sector. In the tech world, the idea of voluntary participation translates into "opting in" (or more often, "opting out") This is usually managed through a deliberately opaque "consent process," which really doesn't describe what's happening if you are barred from the service if you don't sign on. That's not voluntary or consent-driven engagement, that's force.

Civil society should be thinking about processes and using tools that require informed consent and provide the informing. Active consent. What I recently called "Gung ho consent, with an opportunity to stop consenting at any point." As data collection becomes part of everything we use ethicists are already thinking "beyond consent."  As new technological infrastructures like the blockchain come along, there's a pressing opportunity to consider the values that shape them and how civil society can shape their use. And if an individual doesn't want to consent to your data collection processes, do you really want to cut him or her off from your food bank, homeless shelter, museum exhibit or vaccination? In the interest of the greater good, do we really want access to core services to depend on someone's consent to an organization's data processes? That's not what I call voluntary.

When it comes to new technologies or applications of technologies we don't need to go through the pendulum swing of "exuberant hype, omnipresent use, creeping doubt" that has become familiar courtesy of search engine data collection, social media data exhaust, peer to peer car sharing "God views," and wearables that creep us out. There are other approaches.

One way to think about this is to think of tech and data design like we think of electoral district boundary setting. It may not seem as sexy as running for office, but boy does it matter. Gerrymander the district lines and you exert a lot of control over who runs and who wins. Over time and across place how these lines are drawn can come to matter at the macro level - such as the makeup of the US House of Representatives - a body which can ultimately have global influence. All because of how the lines were drawn.

Design defaults in hardware and software are as value-laden as district boundaries. What stays in, what gets collected, what gets stored and where - these decisions nudge our behaviors, at the individual level and at the macro level.

It may seem tough to align our values with the design principles that shape our technologies, but it can be done - on both the supply side and the demand side. The Responsible Data Forum is one example of a "supply-side" approach to tools like this - designing tools with and for communities of activists so that the technological defaults are those of the communities. On the demand side - we as individuals (consumers) - also have power. As Dan Gillmor, a noted tech journalist says, when he chooses tools he wants to put his faith in the values of a community not in a company. If all of civil society thought this way it would dramatically shift the power dynamic between the user of a tech device, the person whose data is being stored in/captured by the device, the device itself, and the designers of the code and hardware. Users would understand what the devices were doing, the device would default to users' choices, and the world of choice in devices would expand.

Bringing these values to bear in the design and development of data processes or new tech tools isn't easy. I was inspired (somewhat ironically) by an observation about how the role of industrial design has changed tech innovation, courtesy of Jony Ive at Apple. In a 2015 New Yorker profile of the company's lead designer, Ian Barker writes:

"Typically, Robert Brunner explained, design had been “a vertical stripe in the chain of events” in a product’s delivery; at Apple, it became “a long horizontal stripe, where design is part of every conversation.”

This is how we need to think about societal values and technology devices. Something that is considered throughout the technology creation process. Not the values of the device makers but the values of the end users and the sector in which the tools will be used. That would lead to technology that serves us, not situations where we need to jury-rig the tools for our ends. Values aligned technology - something to aspire to, especially as digital sensors and networked connectivity become part and parcel of everything.

This is part three of three in a series on digital values and civil society. Part one is here and part two is here.

Net Neutrality Congratulations and Thanks

"The Internet is the ultimate vehicle for free expression."
                               Tom Wheeler, FCC Chairman, February 26, 2015

Congratulations and thank you to the civil society actors who acted to help protect an open internet.

ACLU
Berkman Center
Center for Democracy and Technology
ColorOfChange.org
Common Cause
CREDO Action
Daily Kos
Demand Progress
Electronic Frontier Foundation
Engine
Free Press
Fight for the Future
Ford Foundation
Internet Archive
Knight Foundation
MacArthur Foundation
Media Action Grassroots Network
Mozilla Foundation
National Hispanic Media Coalition
OpenTechnology Institute
Open Society Foundation
Progressive Change Campaign Committee
Public Knowledge
Stanford Center on Internet and Society
Marvin Ammori
Jennifer Granick
Tim Wu
Barbara Van Schewick
and many, many others.

This a key marker of Digital Civil Society. It counts as a victory both for and of the space. The organizations above, most of which are nonprofits, and the hundreds of thousands of people (millions?) who mobilized through these organizations, with these organizations, or simply in proximity to these organizations came together to protect the right to association and expression on equal terms in digital environments. They formulated, organized for, petitioned and persisted in enacting public policy that protects our right to come together and be heard with digital tools and on digital infrastructure. [Here's a new report on how it happened] An effect of the FCC ruling to govern the internet and wireless devices under Title II will be continued fair access to digital space for civic association and expression.

It is also a marker of the arrival of an effective, distributed, diverse set of civil society actors built from and dedicated to a digital environment. The actions that made this policy happen are truly "of" the digital age - they are informed by it, shaped by it, and committed to it.

Essentially, with this victory civil society made its own continued existence possible.

This is not the first time (nor will it be the last) that civil society has preserved it's own potential. The history of public spaces and parks, of the First Amendment, of libraries and information access, of rural telephony - these histories precede today's accomplishment. And the accomplishment is more important because of those roots. It is truly an extension of longstanding, core values of democracy into the digital environment and not the compromise of those values by technological complexity or corporate preemption.

Crowdfunding and philanthropy

A community foundation friend just asked me what's up with crowdfunding? New wine in old bottles or new money? Here's what I said:

"Crowdfunding is here to stay in some form.  I think it's "gateway giving" for folks who live entirely online (now including everyone), will bring in new small dollars that add up, tools for it need to be built natively for mobile devices, and *might* make regular small giving a behavior again for people the way tithing used to be, but won't involve the organizational loyalty of tithing nor will it always be directed to nonprofits."

What's your two cents on crowdfunding and philanthropy?

The Stanford PACS Digital Civil Society Lab is hosting a charrette on civic crowdfunding in May. We're trying to understand where and how crowdfunding tools fit into the overall landscape of private resources for public benefit. Will have more to post here and at the Lab's site.

The giving quants or "algorithmic philanthropy"

I spent the weekend preparing for, and then taping, a segment on digital activism for Philanthropy Talk. That's the public radio "car talk" program for philosophical questions. The segment will air in January.

So it's no wonder that I have thought experiments on my mind. Yesterday when I opened The New York Times (the actual paper edition) I read a range of stories. Sometimes when I read the paper my mind plays tricks on me - like, did the person who wrote the story on page A1 read the story on page B8? Today, several stories in the paper seemed to be speaking to each other - the first one was on robots and jobs. The other one was on artificial intelligence research.

Here's where my mind went (bear with me, this will be about philanthropy and civil society)

First, some background:
This year while I was working on the Blueprint, I kept wanting to do more imaginative work on digital technologies. It's one reason I regularly read newsletters from Edge.org and the Singularity Institute, I go to campus lectures on neural networks and the block chain and other stuff I don't understand and I'm a member of the Long Now Foundation. All efforts to try to learn about far-edge technology. But the far-edge of technology is not the right topic for the Blueprint, since many people who read it are still coming to grips with hashtags and chat apps. So I keep a notebook of thoughts on edgy technology and civil society, trying to figure out what to do with them. This year, one of the pre-readers of the Blueprint said to me, " You know, this is all well and good, but what about the really interesting technological stuff - like neural networks and pattern recognition and AI and robots, and what not?"

So he and I went off and had coffee. And we're trying to figure out what to do with my notes, his observations, and the intersections and implications of cutting-edgier science and technology on philanthropy and civil society.*

Reading the two news stories noted above, I learn that many economists are no longer sure that   technological advances (such as robotics) will create more jobs than they destroy. And then, turn a few pages, and I read about a 100 year study to look at the real effects of artificial intelligence. That is, the study begins now and will run for 100 years. Where will the study take place? Stanford University (with lots of academic partners). It's called AI100

So how do you reconcile these two thoughts - "tech is changing the economy but not augmenting it" with "let's invest now in something to run for 100 years." You make a gift to a nonprofit. Admittedly, a nonprofit with a large endowment, but what is to say that this university (or any institution) will withstand the very forces this study aims to examine? In other words, if you make a 100 year bet to understand a technology's impact, how do you know the technology won't destroy the place you made the bet before the century is up?**

Now, the thought experiment (When AI ate philanthropy)
Assume some folks begin to apply machine learning and artificial intelligence, data and data analytics to the increasing amount of quantitative data being generated by and about social  organizations. This is a completely plausible step from where we are now - what with the effective altruism movement, random control trials, and the emerging data infrastructure for philanthropy. One possibility is such a trajectory leads to the Hedge Fund version of donors - "quant givers." Guided by algorithms and data (replacing program officers and philanthropy advisors) machines would match a donor's dollars with social causes. If we assume that the capacity to do this (at least in the short term) would take a lot of money to build out, we can also assume that the charitable dollars would be coming from wealthy people (or perhaps pools of money from donors, pushing further on the hedge fund metaphor), and so the gifts would also be large. As such, they'd be attractive to organizations, who would try to fit themselves into the models (just as organizations "optimize their search terms" to fit Google search algorithms). Because the algorithms "learn," they get better and better at finding and matching, data crunching and report generating. They create their own, powerful, self-sustaining feedback loop.

It's possible such algorithmic philanthropy could drive enough resources and draw enough attention from fund seeking nonprofits. The feedback loop thus grows to a larger force that begins to change the kinds of measures and metrics that lots of nonprofits track and provide. This leads to behavior change among the vast swath of nonprofits, changing the "marketplace" of options available to smaller, more passion-oriented (or simply less data-driven) donors (i.e. most of us). What would it do to the measures and data that were collected and fed into the machines?

How much would it take before the quant-driven feedback loop affected change throughout the ecosystem of nonprofits? How would parallel movements of impact investing and performance measures, earned revenue and double bottom lines play into this story? How would the more personal, direct-involvement approach of most donors counteract this approach? What countervaling influence could intuition, expression, personal passions, minority voice, and donor choice have on this feedback loop? Just how far can we rationalize/algorithmically structure giving? And how far should we? What if we took all the humanity out of philanthropy?

One likely answer to that question is that the measures would focus ever more on quantifiable, short term outputs that can be easily collected. From the perspective of the algorithm it would be harder to justify longer-term investments in hard-to- measure activities (it would also probably skip over startups with no metrics at all). Long term enterprises and startups might not even "make it into the data" being used by the algorithms.

What falls into this category of long-term hard-to-measure charitable opportunities? Well lots of things like advocacy, policy analysis, and basic research. Oh, and endowed universities.

So, are 100 year research efforts on technological change even possible? How do we factor in the effects of these digital technologies on the peripheral technologies like nonprofit universities that house them? What happens when the thing being researched consumes the place that conducts the research?


SIDEBAR
*What do you think we should do? A new blog? An annual look at just tech and philanthropy? A "hype cycle" analysis? A two by two?
**This paradox, by the way, is one of the reasons I believe so strongly in focusing on the effects of digital innovation on civil society. Most studies of digital change look at their implications for business or government and assume that nonprofits will just keep on keeping on. I think that's nuts.

The Nominet Trust 100 and Social Tech Guide 2014

What do cancer, cow fertility, and civil rights have in common? How about encrypted email, e-democracy, and educational access? Stumped? Here's one more - what about 3D printing, distributed networks of open source building plans, and privacy protecting search engines?

These, and 91 other issues, are areas where people from India to Iceland are combining software, hardware, and people power in new ways to tackle a shared social problem.

100 such ideas are being honored today by the Nominet Trust 100 and the Social Tech Guide. This a curated list of inspiring tech-enabled social good activities.The list and guide are like a "Wow - really?!" list of cool applications of software and hardware being put to use for social good. Proposals came from all over the world - 24 countries are represented among the final 100. The applications were curated first by staff and then judged by an external steering committee (me included).

This is the second year that the Nominet Trust and the Financial Times have curated the list and created the guide. Some of the winners are brand new, others have been around for awhile and have proven themselves. There's sure to be individual applications that make you think differently about your work. And taken as a whole, the list (along with last year's list) provide us with a starting inventory of "digital social innovation."

There's more information about the NT100 and digital social innovation in this year's Blueprint - available for free next Tuesday, December 9, at www.grantcraft.org/blueprint15. 

Check out the #2014NT100 at http://socialtech.org.uk/nominet-trust-100/2014/.

New Power (or lessons for business from the social economy)

(photo: https://hbr.org/2014/12/understanding-new-power)

Henry Timms (founder of #givingtuesday and my colleague via Stanford PACS) and Jeremy Heimans have a new article in the December issue of Harvard Business Review called "Understanding New Power." In it they discuss characteristics such as co-ownership and participatory governance. They highlight some of the values of the new power that they call "opt in decision making" and "open source collaboration."

In the requisite 2 x 2 matrix (this is HBR after all) the precious terrain of the upper right hand quadrant includes a mix of movements (Occupy), nonprofits (Wikipedia), benefit corporations (Etsy), and commercial enterprises.

In other words, several of the institutional forms that constitute what we've been calling the social economy embody the characteristics and values that Timms and Heimanns pinpoint as a new type of power. Go read it - see what you think.

New questions for nonprofits and philanthropy

Among other things, the digital age is bringing us new kinds of nonprofits. I've been talking about this for several years, using examples of the Internet Archive, Mozilla, Creative Commons, and Wikimedia Foundation as "anchor institutions" of digital civil society. Each of these organizations is at least a decade old and each one exists to protect and promote some form of digital asset. If there weren't digital data and infrastructure, none of these nonprofits would (need to) exist.

There are other examples, newer ones, working on newer versions of shared social challenges in the digital age. One of those challenges is privacy. The founder of Privacy International announced today that he will launch a new organization, Code Red, in 2015 that is focused on protecting human rights advocates and whistleblowers in the digital age. This is an example of a social mission particular to the digital age.

Philanthropy is also challenged by attributes unique to the digital age. Take something like this effort to donate satellite imagery - How do we donate something and still own it, which is what happens with digital data? Who owns the data that get donated? is it really a donation or more of a loan? What are the licensing restrictions that will make sense for the donated data? Who is liable for a use of the data that puts someone in danger? These are all examples of questions that we've had answers to when it comes to donating time or money and we need new answers for donating data.

There are also new challenges for longstanding social sector organizations. Domestic violence is one area where the dangers of digital surveillance are keenly felt. There are tools custom built to facilitate stalking and off-the-shelf digital capacities (find my phone, for example) that make tracking people much easier.

What we're facing are questions of how to obtain the public benefit (new medical breakthroughs, new datasets that can inform poverty eradication efforts, whole new resources like up-to-date satellite imagery) of these digital tools without compromising or endangering people. I don't think the math behind this is going to be as simple as weighing one kind of benefit (public) against another (private) - it's going to be some form of multivariable calculus that includes issues of consent, ownership, liability, perpetuity, privacy, and security.

These are the questions that interest me. The ones that represent fundamental shifts in how civil society, nonprofits and philanthropy work. Much more interesting and important than the latest fundraising challenge on social media.

Nonprofits and Cybersecurity

Today's New York Times reveals that the folks who hacked the website of JP Morgan Chase, one of the world's largest banks, also hacked the website and account of the bank's affiliated charity arm - the Chase Corporate Challenge.

In July, GoodWill Inc announced that hackers had accessed information on payments processed by the nonprofit employment program.

Waaaaay back in 2007 hackers breached the security systems at Convio Inc., gaining access to donor information for more than 90 charitable organizations.

Universities have long been, and in 2014 seemed to grow as, a target for cybersecurity breaches.

I'm sure that hospital systems, not-for-profit health care providers, non-profit financial firms, and even philanthropic foundations are also tempting targets.

Why does this matter? In the Chase Corporate Challenge case it appears that hackers were looking for a way into the bank via the nonprofit portal. (NYT says that didn't work. In this case.) In other cases the stash of information - on donors and their financial information - may be tempting enough on its own. For those with malicious means beyond financial interests, accessing information on program participants or program beneficiaries or activities planned may be enough - especially for organizations doing politically, religiously, or culturally sensitive work.

All of this steals the thunder from one of my intended Blueprint 2015 predictions, that hacking, cybersecurity and nonprofits would rise to public attention next year. (Just came on earlier than I thought). 

Cybersecurity and protecting the digital information that nonprofits collect and store is important on the organizational level. It's also important on a systems level. Collectively, given the capacity constraints for most nonprofits and the linked nature of digital data, information breaches from individual organizations can serve as open doors to breaches across organizations and whole sectors. The limited ability of nonprofits to protect information they gather online - even when they outsource the service to third party vendors (who struggle to stay in front of malicious hackers) - makes not just the nonprofits and foundations vulnerable but also their affiliates and partners.

security experts can will tell you what to do to protect your web and digital assets. I think about this more from the programmatic and human side. Too often I see foundations and nonprofits choosing to collect information from people just because they can. It's easy to ask for addresses, phone numbers and email addresses, even when you don't need them and may not know why you would use them. It's easy (and cheap) to store that information somewhere online. And it's easy to forget about it.

We need to shift our organizational mindsets about collecting information from those we serve. We should stop  thinking about information collection as an "all you can eat buffet," where the ease, speed and price of collecting and storing is so low that "more is better." Commercial websites have habituated us to assuming that we have to trade our data (address, birth date, email, phone number and so on) for access.  That's a value exchange and a type of transaction that nonprofits simply don't need to perpetuate.

Any organization that doubts its ability to ensure that it can protect your digital information (i.e. ALL honest organizations) should approach the collection of information with great care. Given our human propensity to re-use passwords we should even consider whether requiring passwords for public access to nonprofit websites makes any sense. Our users will most likely use the same password they use everywhere else, we won't be able to protect it, and - oops - there goes that breach. Rather than the "all you can eat buffet" approach to user information, let's shift to "don't let your eyes be bigger than your stomach." In other words - don't ask for what you don't need. That way, you won't need to worry about having it and losing it. (Or being subpoenaed for it - more on that elsewhere)

Nonprofits bank on trust and integrity. We need to shift our digital behaviors to reflect this when it comes to collecting, storing (and possibly losing) information from those with whom we work.

Apple's Watch and the Ethics of Data

Apple made big news this week with the announcement of its new phones with mobile payment built in and it's new watch, which seems to be a platform for everything from telling you the time to heartbeat sharing (?!)

Much has been written by privacy experts, tech geeks, health policy wonks, and financial gurus about all the new stuff this new OS and device are bringing.

Personally, I appreciated the Cupertino company's doing such a fabulous job of sending a signal that  digital civil society has arrived. (And just in time for our conference on the Ethics of Data - how perfect!)

Here's the signal, in case you missed it. Apple made a big deal about how it can protect your private financial and health data, which the watch and phone will help you collect and manage. They explained how the phone/watch will/will not store your data, how it can be shared, and who will have access to it.

The following language is from Apple's own developer guide - (the rules of the road for the people creating the apps that will make the watch do more than its Casio forebears)

"27.4 Apps may not use user data gathered from the HealthKit API for advertising or other use-based data mining purposes other than improving health, medical, and fitness management, or for the purpose of medical research (emphasis added)"

My question? Medical research by whom? Harvard? (nonprofit) The Centers for Disease Control? (government) Pfizer? (Commercial company) Citizen scientists in their garages? (none of the above)

Medical research is done by businesses, government, and nonprofits. They each operate under separate rules. Some have clear institutional structures and review processes for doing research on humans. Some make sure they have your consent to be included in a study or a publicly reported "finding," others, well not so much.

The New York Times read the above developer guide and interpreted it as if reserving use of the data for medical research was in some ways protecting our privacy. From their Thursday story:

"Apple has made it clear to developers of health apps that it wants to protect privacy. Last week, it updated its guidelines for app developers, stating that apps working with HealthKit, Apple’s new set of tools for tracking fitness and health statistics, may not use the personal data gathered for advertising or data-mining uses other than for helping manage an individual’s health and fitness, or for medical research."

But here's the thing - letting the data be used for "medical research" without specifying by whom and under what conditions doesn't protect you in the least.

It's like saying only "book lenders" will have information about your reading habits. Book lenders include your local library, which has been protecting reader information from prying eyes for decades, and Amazon, which uses your data...differently.

The point is we have different expectations for different kinds of organizations - public, commercial, and not-profit - and we hold them, socially and legally, to different standards of transparency, accountability, and trust. Data cross all those lines (and those lines are already rather blurry). As they celebrated in Cupertino, it's clear that we have entirely new tools for collecting, storing, and sharing our data. We need new rules - especially if we want to maintain the trust and integrity of the nonprofit sector.

What codes inform our work with digital data?

This is the second of a three-part series on the ethics of data in civil society, leading up the Stanford Conference on September 15-16.

Ethical codes abound - here's a list of just a few of them with relevance to how nonprofit organizations or private action for the public benefit.

Asilomar Convention: Ethical decision making in higher education research

http://asilomar-highered.info/

A manifesto for the future of the 'right to be forgotten' debate

http://www.theguardian.com/technology/2014/jul/22/a-manifesto-for-the-future-of-the-right-to-be-forgotten-debate

The Consumer Privacy Bill of Rights (USA)

http://www.whitehouse.gov/sites/default/files/privacy-final.pdf

Compendium of Ethics and Standards for Nonprofits

http://www.independentsector.org/compendium_of_standards?s=ethics

The Data Bill of Rights

http://battellemedia.com/archives/2007/04/the_data_bill_of_rights.php

(A longer, but still not comprehensive, list of examples can be found here)

What, if anything, is different about digital data that requires us to rethink our work in civil society? Here are some characteristics of digital data that may require new ethical choices. 

• Digital data can be collected passively, without knowledge or consent of those from whom the data are collected.
• Digital data enable the application of predictive analytics the accuracy or validity of which are still unknown.  
• Digital data can be stored remotely, and for unknown lengths of time, by third parties who have collected the data or purchased the information.
• Digital data alter the time frame for our actions. For example, real-time satellite imagery lets us adjust our interventions with information never before available. Alternatively, stored data collected from a person today may be used to define actions on behalf of or against that person's children or grandchildren. It can both shorten and lengthen the relevant time frame.

Several scholars have written about ethical provocations of big data, the need for ethics related to big data, and the need for legal due process where big data, algorithmic predictions, or other software applications are concerned. Here are two resources by individuals participating in the Stanford conference.

Kate Crawford and Jason Schultz, Big Data and Due Process: Toward a Framework to Redress Predictive Privacy Harms.

Neil Richards and Jonathan King, Big Data Ethics 

Why "ethics" of digital data?

This is the first of three posts leading up to the Ethics of Data Conference at Stanford. I've posted some earlier thoughts here.

In early August, the New York Times ran a "Room for Debate" series about big data. Over the course of a week columns noting the dangers of digital data use ran next to columns extolling the utility of digital data for community improvement. Other columns in the series, which was titled "Is Big Data Spreading Inequality," looked at how data may be used to extend credit to underserved communites, while others noted that data may be limiting job opportunities. One columnist called for due process related to digital data - an idea that has been studied and proposed by other legal scholars.

Clearly, there's a lot of good and bad that can be done with digital data. How we use it, what bounds we put on its use, what rights we protect regarding its use - these are classic ethical questions now being brought to the forefront where large sets of digital data are concerned.

On September 15 the Federal Trade Commission is hosting a conference in DC on "Big Data: A Tool for Inclusion or Exclusion?" which will focus on how consumers are affected by the uses of big data.

On September 15 and 16, Stanford Center on Philanthropy and Civil Society's Digital Civil Society Lab is hosting a conference on the Ethics of Data in Civil Society. We're focused on what the rise of digital data as a resource and digital infrastructure means for private actions with a public benefit.

The questions addressed in the New York Times series and those that the FTC is asking about discrimination certainly matter for civil society. Two key conceptual resources for the Stanford conference can be found here:

• Framing Document for the Conference
• Provocations on Civil Society Practices and the Ethics of Data

We'll be looking at:

• How data are being used to frame the issues on which nonprofits and voluntary associations work and what civil society can do about it;
• The realities of association and expression in a digital age and what these changes mean for civil society
• How scholarship is changing in a digital environment; 
• The rights of those being served by nonprofits and civil society;
• Ethical dilemmas for civil society organizations using digital data and how to work through them; 
• Ethical ways civil society and industry sources of digital data can work together 

Participants include activists, data companies, nonprofits, scholars, and funders. Conference resources are available here and we'll put post-conference materials there as well.

Cases for Discussion - data, ethics, and civil society

Last year when I wrote the Blueprint 2014 I included a few scenarios regarding nonprofits, foundations and the uses of digital data (see pages 22-23).

Now we're on the brink of hosting an entire conference on the Ethics of Data in Civil Society.

We're pulling together resources from the field and from scholars. I was thrilled when Jeff Raderstrong, now of Living Cities, sent me these Case Studies he and a colleague developed for classes at George Washington University.

   Cases for Discussion BigData by Lucy Bernholz

We'll share these on the conference website (http://stanford.io/ethicsofdata) where you can also find a provocation piece written by Andrew Woods -  Keep checking there for more resources as they become available.

You can follow the conference planning and pre-conference discussions on Twitter at #EoD14.

Thanks for sharing, Jeff and Katlyn.

A new calculus for civil society

In the analog era, when you took action for social good the math was relatively straightforward;
                                 1 action = some result.

It might have been a 1:1 relationship: 1 donation = 1 meal.

It might have been more than that: 1 volunteer act = multiple additional donations = multiple benefits

It might have included a multiplier effect: Action sustained over time = new policies = multiple benefits

It might have backfired: 1 action = negative result

What it didn't have, and part of what makes digital action different, is a "digital differential."

Here's what I mean. In the digital environment, every action creates a digital trail - data, metadata or both. So if you click to like the ALS Ice Bucket challenge (for example, to be au courant) your click supports ALS research.  It also tells your friends you care about ALS (or that you are very much in the know), it also adds to the dataset of information about you that is being built by several enterprises and held in several places, and it also adds to the dataset of the ALS campaign.

Your single click becomes a digital data point with lots of potential other uses (marketing, donation solicitation, friendship building). One action = lots of derivative uses and interpretations, some by you, most by others.

This digital differential is true for all digital data. Our actions in digital space create an additional "resource" (data) that can be used in lots of ways. These digital differentials may be used for positive or negative actions. What happens with them is not inherent in the data, it will depend on what we do with the data and how we do it.

CrisisTextLine is a great example of this. It helps crisis counseling centers reach teens via text. In the analog age (last year) when this was done by phone, the math was straightforward:

ANALOG: 1 call = 1 teen helped.

Today, the math is different:

DIGITAL: 1 text message = 1 teen helped + a dataset of digital text messages (with more than 3 million records to-date).

This is one way (there are others) that digital changes the calculus of civil society.

What do you do with that dataset? How do you protect it and the rights of the people represented within it? CrisisTextLine hopes to make it useful to scholars and policymakers. You can see their work - and their ethical decisionmaking, struggles, and open questions about this here.* The upcoming Ethics of Data conference will look at these questions and many others in a broader civil society context. Some of the thinking on data philanthropy also addresses these issues.



*At the Digital Civil Society Lab at Stanford, we held a charrette around CTL's work - because their opportunities and challenges are all of ours, they're willing to share them publicly and ask for help, and we all stand to learn a great deal from what they are trying to do and how they are trying to do it.