Thanks for your explanations!
Apologies…I mean the questions your team decides upon during your research and interview processes (not the initial prompt/project question). As generalist, do you ever work with domain experts to help frame the questions (not just get answers)?
Re: Audit tools
I realize that tools might have sounded like software or something, but I’m thinking more of frameworks that can help to weed out potential biases in data sets (ex. algorithm bias, clustering illusion, etc.), studies (ex., publication bias, parachute science, etc.), and individuals (ex. cognitive bias(es), appeal to authority, etc.). I’m not suggesting you encounter these specific biases with your research, but I imagine there are known (and unknown) biases you have to check for and assess.
Re: Possible approach for less bias
Again, I’m not a professional researcher, so I don’t want to assume I have anything novel to add here. That said, when I read about research and/or macro analysis, I see a lot of emphasis on things like selection and study design — but not as much on the curation or review teams i.e. who decides?
My intuition tells me that — along with study designs — curation and review are particularly important to weeding out bias. (The merry-go-round water pump story in Doing Good Better comes to mind.) You mentioned sometimes interviewing differing or opposing views, but I imagine these are inside the research itself and are usually with other academics or recognized domain experts (please correct me if I'm wrong).
So, in the case of say, a project by an org from the Global North that would lead to action/policy/capital allocation in/for the Global South, it would seem that local experts should also have a “seat at the table” — not just in providing data — but in curating/reviewing/concluding as well.
With this post almost a year old now, I was curious if any of the commenters who were interested in switching to EA-related work have pursued this route. If so:
- Have you been hired?
- What was the job seeking process like for you?
- Any recommendations to other mid-career professionals looking to pursue this path?
Thanks for sharing. I'm not a professional researcher, but spend a fair bit of time researching personal projects, areas of interest, etc., and enjoy learning about different exploration frameworks and processes. As a generalist myself, it can sometime be difficult to know if you're adding signal or noise to a picture you've yet to fully envisage -- particularly where a high-level of outside domain or technical knowledge is necessary.
In my experience, beneficial answers are often the result of pinging the right sources with the right queries. This alone can be a difficult chain to establish, but there's a deeper layer that strikes me as paradoxical: In most cases: the person/team/org seeking knowledge is also the arbiter of information. So...
- How do you determine if you're asking the right questions?
- What is your process for judging information quality?
- Do you employ any audits or tools to identify/correct biases (e.g. what studies you select, whom you decide to interview, etc.)?
Thanks for the referral. Interesting post -- even if much of the technical-speak is lost on me. What I gathered is that nobody really knows if/when software engineering will become an unskilled job (no surprise) but, a) many are confident that it won't be anytime soon (at least, for the discipline as a whole), and b) junior developers are the ones that LLMs are likely to replace (est. 1-3 yrs.).
While much of the thread's early sentiments echo replies here, there's a divergence concerning newer engineers as the conversation continues. It's these bearish predictions that worry me. I don't need to make six figures, but I can't invest time (6-12 mo.) and money (courses, bootcamp, etc.) in a career path where newbie "escape velocity" is unlikely. More to think about...
No, I've already made the decision to leave copywriting (unless an opportunity to have an incredible impact came my way).
Software engineering and data science were the two paths I was considering but engineering won out 1) As an end-to-end (idea to product) creation tool, and 2) Iit doesn't require me to first become proficient in probability/statistics . The latter is something I eventually hope to do but, financially, I can't afford to ramp up in math, then data science, then find a job. And while it's estimated that data science roles will grow at a faster rate than jobs in software engineering, there are far less overall spots available in data science . Being at the midpoint of my career, my ability to make a meaningful contribution somewhere as a software developer seems more likely than as a data scientist. Lastly, I'd assume data science would be the type of skill that AI will replace before software engineering (but that's a huge guess).
Thanks for that perspective. Given that I don't have experience in the programming space, I couldn't project a timeline between fully automated software production and AGI -- but your estimate puts something on the map for me. It is disconcerting though, as there are many different assumptions and perspectives about AGI, and a lot of uncertainty. But I also understand that certainty isn't something I should expect on any topic -- let alone this one . Moreover, career inaction isn't an option I can afford, so I'll likely be barreling down the software dev path very soon.
I'd say marketing is business-critical, and the difference between phone-it-in, good, great, and stellar content is important to bottom lines (depending on industry/product/service). That said, if the general point is that grammar issues on a site will have a lesser negative effect than buggy code that crashes that site, I agree. I'd also agree that unless you're a marketing or content agency, marketing and content may be part of your business but they're not the core of it. In contrast, almost every business in every industry runs on software today...
Still, I don't know how long things like scale, complexity, and strategy will be meaningful hurdles for LLMs and other AI technology (nobody does), but it feels like we're accelerating toward an end point. Regardless, software engineering seems like a good aptitude to add to the toolbox, and it's good to hear that I may not be too late to the game.
When it comes to refining AI generated code, do you imagine this being done within organizations by the same amount of programmers or that LLMs could be managed by fewer senior (or even lower) level engineers? This question is inspired by my observations in marketing, where the stock of full-time writers appears to be going down. I totally get that LLMs can’t create their own prompts, debug every line of code, or approve products, but do you think they’ll start allowing orgs to complete product development cycles with less engineers?
Great point that coding isn’t an end in itself. In addition to seeming fun/interesting, I'm looking to learn this skill for greater domain range, technical building ability, and professional autonomy. Knowing how to code could eventually help me launch a startup or support an EA-related org. And yeah, earning to give while I ramp makes this path even more attractive. Many great points and thanks for the encouragement!
Very interesting point. I hadn’t seen this as super plausible given how AI is starting to be used in copywriting/marketing: 1) Copy editors can now give prompts to LLMs and refine from there. 2) Non-writing workers e.g. marketing coordinators, account managers, etc. can use LLMs to create “good enough” pieces for landing pages, social captions, SEO, etc. This kind of AI integration seems to be eliminating the need for copywriters, content writers, brand writers, etc. But I should acknowledge that a lot of my worries are based on anecdotal evidence. I was the only full-time writer at my previous agency and, while I left on my own accord, it looks like they're going to experiment without the position. I think their plan is to get non-writing account managers proficient with an LLM and contract with a lower level writer for client edits.
According to BLS, writers and authors (very broad category) are expected to grow at 4% over the next 10 years, while editor roles are expected to decline by 5%. I do imagine that copy directors, technical writers, and script writers (various levels) will be among those spared near future replacement, but these are very specific niches, and the ability for LLMs to craft slogans, taglines, and scripts is getting quite impressive...
Now, I understand content creation is quite different from software engineering, and perhaps the former positions and tasks don't map well onto the latter. To your point, maybe the transformation in software is more analogous to physical engineering, where a newer professional who knows SOLIDWORKS, Fusion 360, FDM/3D, etc. is going to add value where someone more experienced who only works with legacy programs and traditional manufacturing can't. Does that comparison feel appropriate?
Give a man a fish and he eats for a day. Teach a man to fish and he’ll have to buy all of the lures, tackle, and rods you taught him how to use. #capitalism #25%offyour1storder #overfishing
Submitted my real suggestions through the form...
Can we submit more than one idea per form or should we do a new form for each proverb suggestion?
Thanks, Adam! And thank you for starting a conversation around this approach (I don't think I mentioned that in my original comment). I've actually applied to some of the new comms positions at CEA and would love the opportunity to further explore these ideas and others...
Location: Los Angeles, CA (United States)
Willing to relocate: N
- Marketing strategy
- Content creation
- Creative direction
- Project management (intermediate)
- Operations (limited)
- Business development (limited)
- Graphic design (intermediate)
- Video editing (intermediate)
- Website and social media management (limited)
Email: inkodachrome ( — at the dot come of — ) gmail
- While the bulk of my background is in content and marketing, I'm also a former founder with business, operations, and sales experience. Usually hired for one role, I'm often shifted over to a generalist position that connects multiple departments and/or business areas. I'm interested in expanding my skills to include data science and coding.
- I work well solo or in a group and love solving difficult problems!
- Open to various cause areas with particular interest in longtermism, s-risks, civilian resilience, and global priorities.
- Preference for a full-time position.
- Available two weeks from offer.
- I’m somewhat new to EA, but have done an 80,000 Hours advising session and am currently scripting a video piece for Giving What We Can.
Congrats on the new site! I'm excited to check it out!
I feel compelled to offer feedback on the new mission statement — if only to improve communication and comprehension.
“Our mission is to help others as much as we can with the resources available to us.”
It’s a short and simple sentence, but I believe it would be unclear to many unfamiliar with Open Phil or EA.
The statement doesn’t say what you do to "help" others, which could be interpreted as anything from grants for college to lobbying on healthcare to a smoother commute.
Similarly, “resources” is only contextualized by “available to us.” This doesn't really give the reader any information.
This is probably nitpicky, but “as much as we can” changes the rhythm of the sentence (up and down), and takes up too much space for its purpose.
The impact (or results) of your work is also missing from the statement I.e. “We help X do Y to achieve Z.”
Ideally, you should be able to put your mission statement on your homepage and a new visitor would know exactly what you do and why they should lean in to learn more. I don't think this statement does that.
Here are some ideas:
- "Our mission is to leverage accessible resources to improve the lives of others."
- "We leverage existing resources to improve the lives of others."
- "We deploy available funds and useful resources toward bettering people’s lives."
- "Our mission is to use radical empathy and innovative ideas to better others' lives."
- "We combine data, resources, and empathy to improve the lives of others."
- "We help improve the lives of others through data, resources, and empathy."
- "Our mission is to direct more attention and resources to better others' lives."
These were quick sketches, so I'm not advocating for any one in particular -- and it’s not my intention to take liberties with any of the crucial information in your mission statement. (For example, you may have intentionally put “others” instead of “people” as a way to encompass all living beings.) The samples are more for springboarding ideas that could help you develop and refine the statement a little further.
I think this is a great idea and -- as a newish member here -- am surprised it's never been attempted.
Some additional thoughts...
While the terms "celebrity" and "influencer" can sometimes be used interchangeably (and crossover does exist), the marketing world often views the two personas as distinct. There has been some research on the differences between the "celebrity endorsement" and "influencer recommendation" with influencers often delivering better results. This is supported by micro influencers often getting higher engagement rates than much larger influencers and celebrities.
You can use this tool to not only explore the engagement rates of different Instagram influencers, but also the cost of partnerships. Here's a quick comparison between Justin Bieber and The Physics Girl :
- Followers: 233M followers
- Posts: 7,122 posts
- Estimated Cost Per Post: $463,948 - $773,246
- Engagement Rate: 0.18%
The Physics Girl
- Followers: 146,489
- Posts: 716
- Estimated Cost Per Post: $439.89 - $733.15
- Engagement Rate: 3.51%
Even with the lower engagement rate, you're still going to get massive exposure through Justin Bieber. However, audience match and behavior should still be considered when estimating CR (conversion rate):
- Is the cause/message likely to resonate with the celebrity or influencer's audience?
- Are members of the audience likely to take action around the cause/message?
This idea of "niching down" can also be applied to the cause area or organization. In other words, instead of a celebrity or influencer endorsing EA, they could instead promote specific EA-related causes or charities e.g. global poverty and health or Giving What We Can, AI alignment or The Future of Life Institute, etc. EA, as a cause area and philosophy, has a bit of a learning curve attached and some/many people might not want to put in the work -- losing them as potential advocates along the way.
On the other hand, a specific cause or charity is likely easier for the uninitiated to understand and support. Some examples of messaging (celebrity voice)...
- EA - I support Effective Altruism -- a social movement and philosophy focused on maximizing the good you can do in your career, projects, and other life decisions. Learn more and see how you can get involved as well! (link in bio)
- Global poverty and health - I believe helping people in low-income countries is the best way to focus my philanthropic efforts. See why I give and how you can get involved as well! (link in bio)
- Giving What We Can - I just took a pledge to give 10% of my income to help fight global poverty. Find out how you can get involved as well! (link in bio)
Each of those blurbs could be punched up, but I tried to keep the last lines as close as possible for a more apples-to-apples comparison (subjective as that may be). There are pros and cons to each but, generally, the more targeted, clearer, and specific a message, the higher its engagement and CTR (click-through rate). Still, you'd want to test variations across audiences, cause areas, and CTAs (calls to action).
All of that said, I think celebrities/influencers promoting EA would be mostly good. My guess is that going more granular with aligned influencer audiences would produce better quality and longer lasting results.
A lot of interesting points here. “Like to like” can be a great approach. In addition to the shared persona, this technique can also help inform distribution. For example, LinkedIn comes to mind as a place for leveraging network effects. That said, Facebook Groups, Subreddits, Discord Channels, and other niche communities could produce higher engagement rates.
Still, while a shared profession might prequalify a reader, offer the creator special access, and/or hold an audience’s attention longer, crafting meaningful content remains a key difficulty. You mention, "articles would differ in addressing the particular concerns of people in that target group," which is a solid goal. However, targeted content can often be reduced to baseline commonalities. So, a potential downside risk with professional targeting is writing toward a job title rather than a person.
Using the example, "How this software engineer approaches charity” -- noting that this is likely a placeholder title -- I’d start developing the content by asking:
- Who is the piece for?
- What does the piece hope to accomplish?
At first glance, the title indicates that the article would be written for software engineers. However, it could be argued that this is more the intention of the author and that the audience is really people who might be interested in this particular software engineer’s charitable musings. So, unless the software engineer is a thought leader or influencer in their space, this content might be too niche to achieve a sizable impact. Conversely, the article might intrigue someone generally interested in giving and charity, but the specificity of the software engineer makes it less tailored for them.
When designing both titles and content, I find it helpful to shift perspectives from writer to reader. Here are some questions I use:
- Why is this piece of content interesting to the reader?
- How does it speak to their personal goals or pain points?
- Does the piece offer value and/or provide solutions?
- Is the message engaging…helpful…meaningful?
Using these questions, one might arrive at titles like:
- How I Made Software Engineering a Fulfilling Career (Audience: Engineers looking for meaning through their career)
- Giving Like a Coder: How I Hacked My Charitable Contributions (Audience: Engineers looking to optimize every area of their life)
- How You Can Maximize Impact as a Software Engineer (Audience: Engineers looking to do more through their career)
- How Software Engineers Can Save Lives (Audience: Engineers interested in doing important work)
- Top 10 Software Engineers Who Are Giving Back (Audience: Engineers aspiring to be like their respected contemporaries)
While I employed some hooks with these titles, I’m shaping through the lens of a software engineer presumed hopes, interests, issues, etc. — not just the shared persona. You can pull this out further and see how each title could then fulfill on the promise of its premise and, ultimately, align with the second question: “What does the piece hope to accomplish?”
All of that said, the content that might result from a framework like this could have its own downside risks:
- Disingenuous writing: Tailoring too much for an audience and/or applying marketing best practices (hooks, keywords, SEO , etc.) has the potential to compromise core messaging.
- Low fidelity: Due to its often "snackable" nature, viral/shareable content can lack important nuance.
- Unrepresentative associations: A successful article could be shared by the unengaged for purposes such as virtual signaling, risking the reputation of the EA community and/or appropriation of EA-related indicators e.g. #effectivealtruism.
You mention some of these risks in your post, so perhaps additional guidelines should be considered when pursuing external targeted movement building.
All of that said. I think professional outreach + meaningful content has strong potential to reach and activate people.
Thank you to Charity Entrepreneurship and all contributors for putting this book together. Can't wait to read!
I just applied! Thanks in advance for your consideration!
Educate, empower, and enable diverse talent to work on solutions for the world’s biggest issues.
What is it?
A remote school offering tuition-free education and job placement for vital roles (data scientist, researcher, engineer, etc.) in areas of crucial need (climate, economics, healthcare, etc.).
- Identify important areas where key talent is lacking.
- Establish tuition-free online school led by top thinkers.
- Dispense task-oriented knowledge in short period of time.
- Create post-graduation job placement program for sectors in need.
- Remove barriers to higher education.
- Create access to opportunities, regardless of location, language, background, etc.
- Lift people out of poverty.
- Funnel talent into organizations and projects that need the most support.
- Solve range of vital issues.
- Grow pool of world problem solvers.
- Inspire next generation of doers and founders.
- Open up to more students, more languages, more education levels, more areas of speciality.
- Create accelerator program to invest in alum startups.
Two things that scale well are knowledge and technology. So, rather than attempt to choose a single area of focus, create a megaproject that both democratizes pursuits and crowdsources solutions. This has the potential to produce a network effect on a variety of problems, while removing hierarchal barriers. Scaling continues until new talent declines to join and/or roles disappear, or problems are solved (due to lack of new focus areas and/or some yet-to-be realized superior option i.e. ML/AI).
- Lambda School https://lambdaschool.com
- Y Combinator https://www.ycombinator.com