Category: Operations

AI does not excite me, it worries me. Everyone (or nearly everyone) has been jumping into the AI bandwagon like it’s the biggest invention since the steam engine, but I find it absolutely underwhelming at best, and frightening at worst. I have tried to integrate it into my grant development workflow, but my skepticism has only deepened.

Don’t get me wrong, I’m no techno-Luddite. In fact, the opposite is true: I’m a techno-geek who laps up news about tech innovations, both of the hardware and software kind. Ever since the PC was invented, I have been addicted to chip-run machines and other gadgets and would save money to buy the latest ones just to try them out (and sell them later). I also dabbled in web development – teaching myself Joomla, Drupal, WordPress and SMF, then setting up websites for my friends. I loved Free, Open Source Software (FOSS) when everyone I knew was content with Windows and MS Office, trying out the latest Linux distros and related ecosystem apps (LibreOffice, GIMP, etc.) and installing them in my friends’ computers (and occasionally at the workplace). When CRMs came along, I got excited too, as I found them very useful for my profession as a nonprofit fundraiser.

When the buzz about AI started, I tried them out and was immediately puzzled. Why are people enthralled over a software that basically summarizes people’s ideas and data outputs, and then spews them out on a query without even vetting their sources? I have been doing research for as far back as I can remember, and for me this is a dangerous habit. I also knew that such software is only as good (or bad) as the information it absorbs, even preserving biases and prejudices that its creators have.

My skepticism went further downhill when the “Godfather of AI” himself, Geoffrey Hinton, voiced out fears on its lack of regulation and its rapid progress, which may lead to AI models possessing levels of knowledge that would make human intervention absolutely unnecessary. “If you want to know how it’s like not to be the apex intelligence, ask a chicken,” he reportedly said in a BBC interview. Some of its biggest developers, including Elon Musk, also voiced out similar apprehensions on AI’s unregulated growth.  

Apparently, investors are excited about it for the biggest potential it holds: automation and labor cost-cutting. The prospect of increasing profits through workforce redundancy is always something that whips up bubble-making frenzy among venture capitalists, unemployment and recession be damned. This lemming-like rush to throw money at AI development is the reason for its phenomenal progress, with even the nonprofit sector being pressured by CSR funding hints towards integrating AI into their operations.

I was once asked in a job interview for a fundraising role: “How do you aim to enhance the use of AI in fundraising for us?”

Despite finding that question ineffably weird and being tempted to answer “I don’t,” I mumbled something about already using AI when I do Google searches. Because you see, I feel insulted that I would need to run to AI to write a grant proposal narrative, for instance. Or worse, turning to AI when I need to do research on high net-worth individuals. Call me old school all you want, but I am proud of my ability to fundraise without needing biased suggestions from a software. I got enough brains and experience to do that by myself, thank you.   

Needless to say, I didn’t get the job. But I kept my dignity and self-respect.

Corporate Social Responsibility (CSR) is a private sector philosophy and platform conceived by big business as a way for them to “give back to society”, even while it also serves as a convenient conduit for soft marketing and tax reduction. It was promoted as a win-win solution to the big business conundrum of untrammeled wealth accumulation amidst widening social gaps in countries where they operate.

Before CSR became widely accepted from the 1990s onwards, it was assumed that nonprofits/NGOs and the private sector belong to two separate silos: the former provides social services for marginalized and vulnerable sectors of society, while the latter creates profit for private wealth accumulation. Despite efforts to marry the two disparate social functions, their fundamental difference remains: one is concerned with the equitable distribution of social wealth, while the other is focused with its private accumulation. This distinction is reflected in their respective cultural and operational norms.

Now that CSR has become a standard among big business players, the line between the two threatens to become increasingly blurred as corporate norms continuously permeate nonprofit culture and influence their operations. This creeping corporatization occurred mainly through two streams of influence.

The first one is a giving culture that requires NGOs receiving CSR funds to deliver exemplary ROI (“best bang for the buck”), and through impact metrics that closely aligns with those of corporate donors. In time, business framing became the nexus of understanding between giver and receiver, gradually transforming the qualitative-focused management culture of nonprofits into one that conforms (often awkwardly) to the tyranny of hard numbers (“measurable impact”). The same level of compliance extends across corporate and philanthropic foundations, which are established and operated by big capital.

The second stream of influence is operational and developed naturally from the first, mainly manifested by a preference for hiring ex-corporate staff. Since nonprofits receiving CSR funds are already sold on the benefits of having a businesslike culture in the workplace, it became seemingly logical that ex-corporates make for good NGO staff material. This assumption ignores the reality that having come from a profit-oriented environment that pays much higher salaries does not necessarily predispose ex-corporates towards social justice work and the altruistic commitment it requires. In the short term, this bias will likely result in hiring mismatches that can lead to long adjustment periods, lackluster performances and quick staff turnovers. In the long term, such a human resource mindset risks converting nonprofits into corporate doppelgangers run by overly transactional Boards and leadership teams.

Balancing between the need for corporate efficiency in NGO operations and preserving its humane culture (its “soul”, as some would have it) can be tricky. One does not preclude the other, but too much of either can undermine a nonprofit’s strategic goals. Striking the right formula means leaning primarily on empathetic social service rather than operational efficiency, while absorbing elements of corporate dynamics only as absolutely necessary. After all, what defines nonprofits is their humanity and quest for social justice, not fidelity to the imperatives of ROI and wealth accumulation.