News and analysis
December 09, 2015

Philanthropy’s 2015 Buzzwords: From ‘Effective Altruism’ to ‘Worm Wars’

In just a few days last week, everybody in philanthropy was suddenly talking about limited-liability corporations. It quickly became clear that LLC, the approach adopted by Priscilla Chan and Mark Zuckerberg to house the Facebook shares they are earmarking for social good, would be one of the dominant buzzwords of 2016.

Since 2007 I have been putting together a year-end list of 10 phrases that not only tell us what’s new in philanthropy but also point to what’s coming next — that indicate how we’ll all be talking and thinking. Many of these buzzwords are new and notable; others are ones that nobody thinks twice about using anymore.

But in every instance, the words speak to trends that no one in the world of philanthropy should ignore. In 2015, I’ve included phrases that demonstrate how important evidence and effectiveness have become to many nonprofits. Other terms represent technological advances, in areas such as genetic and data science, that are providing new tools that will have profound implications for both individual privacy and collective action.

Ignoring these developments, and failing to understand the language, are risks that philanthropy and society cannot afford to take. More about the impact of these trends on philanthropy can be found in a report the Foundation Center and I are releasing today, "Blueprint 2016."

Here, listed in order of buzzworthiness, are the words that defined 2015. I hope you’ll share your best buzzwords in the comments section below.

1. "… for Good." The creation of the charity-donation site Network for Good in 2001 not only heralded an age of new giving tools but also gave us a term we’d soon be unable to escape. We now have social media for good, coders for good, search engines for good, magazines for good. The only thing I haven’t seen is "Evildoers for Good." As a buzzword, the phrase " ... for good" has so pervaded our vocabulary as to become genre-defining, like the role of love in pop music or car crashes in action films.

2. Overhead myth. This is the name given to an oversimplified measure that uses administrative costs as a meaningful indicator of organizational effectiveness. Watchdog groups that seek to inform donors perpetuate this measure, even though they often include qualifiers about its limited value in small print on their websites. In the last few years, a coordinated effort to debunk the importance given to administrative costs has gained significant traction, leading to a bit of a rhetorical and behavioral standoff. Nonprofits, foundations, donors, and charity-ranking sites all discourage attention to overhead costs ratios even as they continue to report them. Nonprofit overhead costs are like rubbernecking; we know we shouldn’t look, but we just can’t help ourselves. Darren Walker, president of the Ford Foundation, rechristened this idea the "overhead fiction" in a letter this fall that outlines his organization’s new direction.

3. Effective altruism. Not to be confused with "effective philanthropy," the effective-altruism movement has its roots in utilitarian philosophy and has been advanced mainly by modern-day leaders like the Princeton professor Peter Singer and the Oxford philosopher William MacAskill. The movement’s bumper-sticker tagline "Do the most good" conveys the basic goal of applying rational calculations to achieve the greatest returns for charitable gifts. Proponents and detractors abound. Like it or lump it, effective altruism offers intellectual shape and a set of principles to the long-brewing but inchoate attention on metrics, data, and outcomes.

4. X-risks. Shorthand for "existential risks," these are the biggies — the things that could wipe out humanity. A report from the Global Challenges Foundation listed 12 terrifying possibilities, ranging from artificial intelligence run amok to catastrophic climate change to pandemics to synthetic biology. Each one of these forces could wipe out current human populations and preclude any potential offspring, wiping out the species known as people. The likelihood of catastrophic climate change is great enough that cost-benefit calculations argue for taking steps now to prevent it.

5. Platform co-operativism. In the last few years, the sharing or peer-to-peer economy has become familiar to almost everyone. Most of the focus on Uber and Airbnb has been on their effects on taxi services and hotel industries, but the idea of sharing community resources has deep roots in the nonprofit world. In the last year, innovators in nonprofits and elsewhere have begun to "take back" the idea of shared services. One manifestation is platform co-operativism — a type of sharing service (think cars, apartments, or bicycles) in which both the inventory and the technology systems are owned collectively. It’s one more sign that the future of work is in flux. When the cooperative-enterprise structure meets high tech (see Loomio, Ethereum, and the Enspiral Network), it’s a good sign that new governance models may be on the horizon for the social economy.

6. Worm wars. We’re all familiar with philanthropy’s growing interest in randomized control trials and evidence-based social practice. But what if the scientists don’t agree? That’s what happened when research studies that seemed to show the effectiveness of deworming medication on young people’s educational and health indicators were replicated and the results varied. The resulting battles over the science were dubbed the worm wars. The alliterative name helped attract media attention. The more philanthropy seeks to rely on evidence, the more it’s going to find itself caught on methodological battlefields.

7. Algorithm. We’ve learned to think about data; now we’re realizing we also need to think about the algorithms by which we analyze or manipulate the data. Who’s creating them and how do they amplify existing biases? What, if any, recourse do we have if algorithms discriminate? The truth is that all the data and analysis we’re now capable of producing isn’t making things simpler or more straightforward. Instead, it’s demanding a new kind of data literacy, giving rise to new sorts of "data intermediaries" and requiring new forms of oversight and interpretation.

8. Augmented reality. The Oculus Rift and other virtual-reality headsets get a lot of attention, but these are still a generation away from adoption by anyone who doesn’t want to walk around wearing what looks like black-tinted ski goggles. But augmented reality — in which digitized information appears in view alongside the real world — is already here. Cars with directions projected from the GPS to the windshield are one example. We already spend hours everyday staring at our phones; soon we’ll be pointing them at everyday objects (and other people) and getting all sorts of information about whatever is in view.

9. Biononymity. It’s not just cameras, ID-card scanners in buildings, and license-plate readers that are tracking our every move. As DNA analysis gets better and cheaper, our lack of "biological anonymity" is coming to the forefront. Artists use "found" DNA from stray hairs on subway cars and lipstick taken from tossed-out coffee cups to create remarkably accurate drawings and three-dimensional representations of commuters who have passed by. Lawyers, artists, biologists, and technologists are coming together in an informal network known as to proactively consider the implications of this creepy new reality.

10. CRISPR. What if you could cut and paste genetic material with an ease equivalent to word processing? Well, now you can. A new system for genomic editing — specifically, cutting and pasting "clustered, regularly interspaced, short palindromic repeats," or CRISPR — now exists. The technology is the subject of both scientific and corporate battles, but its influence comes from its low cost and widespread availability. While we’ve been focused on digital hacking, gene hacking is about to become a real possibility. It’s entirely likely that biological systems are about to follow a similar trajectory of deinstitutionalization, "freelance science," and hard-to-regulate spaces that have marked the last decades of digitization.

Lucy Bernholz is a senior research scholar at Stanford University’s Center on Philanthropy and Civil Society, where she is one of the leaders of the Digital Civil Society Lab. This piece is adapted from her new report, "Blueprint 2016," released today by the Foundation Center.