I don't know about CS conferences but I've heard people complaining about free software conferences with a lot of Big Tech sponsoring where speakers were kindly requested by conference organizers not to talk too much about subjects "that may upset the sponsor" and things like that. If there's that kind of forces at play, then it is quite detrimental to receiving objective information.

I have attended a few PyCon, and fleetingly visited/watched several similar conferences. There seems to be enough instances where presenters have pressed companies like FAGMA to correct certain implementations in their product stack. Even CPP conference has on several times called out MS VC++ on their compiler peculiarities in the distant past. Whitehat security conferences are usually full blown on the offensive in showing how compromised some platforms could be. I am not discounting your concern, but unless evidence exists, this could be more hearsay or anecdotal.

(I dont work for any of these companies and on several occasions declined to interview. Full disclosure: no relationship).

It's hard to provide evidence for this type of thing, but it's very much a concern to be believed. Companies giving you a corporate sponsorship will definitely influence your decision making. Always. Choices are made, often literally behind the curtain, to appease them. Seeing a few public examples of push back doesn't eliminate this fact.

(Full disclosure: I am an indie conference maker [0], so I'm biased against corporate sponsors.)

[0] https://handmade-seattle.com

> Whitehat security conferences are usually full blown on the offensive in showing how compromised some platforms could be.

Until recently it was common for sponsor companies to threaten conferences to pull talks that demonstrated security flaws in their products. They’ve realized that the PR hit from this usually outweighs any “benefits” now but it used to be a whole thing.

I'm honestly not sure that a conference stage is typically the most appropriate place to go after companies for specific issues. I can think of one of two examples where (to me) it was called for. But I certainly wouldn't want it to be the norm.

ADDED: What I mean by this is that a conference filled with talks where people are badmouthing competitors or others sounds pretty unpleasant.

What kind of a subject can upset a sponsor in a CS conference?

You are saying that the risks of industry interests have not come true. There has been much talk about companies trying to influence what products are being used in education, which for universities, is closely related to research. Even if we assume this to be true a risk that has not happened (much) is by no means guaranteed to not happen in the near future.

Also the examples that you name "bandwidth compression, codecs, recommender systems, crytocurrency" are really quite sexy. They sound like things academics would research all on their own without corporate involvement. The thing is that basically these things can be researched if one just has a computer, or in the case of bandwidth compression, a few computers, and enormous amounts of money are not really necessary so the corporate involvement would not seem to be strictly necessary. And then, when a corporation is involved one runs the risk of the findings disappearing behind a copyright or a patent wall. It is much better for all of us if they become available to everybody. That is, by the way, one of the reasons to have academia in the first place.

> There has been much talk about companies trying to influence what products are being used in education, which for universities, is closely related to research.

I will speak for ML & Systems. I am not an expert on all domains. Most tools that researchers use in ML are open-sourced e.g. Pytorch TF Keras etc. Foundational papers like GFS, BigTable, Hadoop etc are publicly available now. There is a moratorium on how soon it appears, but it isn't behind walls forever. Academia tends to choose more open source over closed source. I'd have argued MATLAB to be more successful than Python in that case. It is not. In industry the practice may be more of 50-50 or even more towards closed source.

> They sound like things academics would research all on their own without corporate involvement. The thing is that basically these things can be researched if one just has a computer.

How can you emulate operation involving scale with just a computer or a bunch of computers. Hence, that is where industrial efforts come in play. A lot of things work well for a dozen, and then a completely different problem emerges when we talk about hundreds or thousands of users.

I am only alluding to the fact that CS, in contrast to many other disciplines, has a more symbiotic relationship with industry. Companies do have incentives of using copyright & trade secrets, but there is enough trickle-down effect that gives academia to pursue newer challenges. The cycle repeats over and over. Academia cannot replace industry and likewise. If there is any pressing problem of this symbiosis, it is more of labor attrition. More people are leaving academia for better pay. But that is not what the topic was about.

> And then, when a corporation is involved one runs the risk of the findings disappearing behind a copyright or a patent wall.

True, but universities often patent algorithmic (and other) discoveries and try to charge companies for implementing them as well.

> "CS research will be guided by industry interests". This is good to most extent, save a few very remote situations.

You start out with a pretty strong statement there...

The point (for me) is not so much that a single company might try to push through some evil villainous plan. It's that all the companies that tend to sponsor such conferences (or more generally "guide" the research) have specific incentives.

Take as the most glaring example the way that machine learning and statistics have been developing over the last years. The industry has an interest in collecting and knowing as much about their customers as possible. Most prominently, facebook and google are both pretty openly based on surveilling every detail of their users' (and everyone else's) lives.

ML research has been co-developing with this. The big money (grants, hardware support, PhD funding, conferences, ...) has been overwhelmingly in domains that directly benefit these players. A lot of "cutting edge" research at the moment is of little benefit to anyone who is not a surveillance capitalist megacorp, simply because of the compute & datasets needed to power these methods. "Causality" has been a big topic over the last years. And yes, it will benefit a lot of things. But where does the actual research start? With the question "why did the user click that search page ad, and what ad should we show them next?"

Sure, there is a little research into privacy preserving ML, into "small data" ML, into federated learning (i.e. user-centric ML, not "distributed training" as in spreading computation over a big corp's cluster) and you can always argue "yeah but in a few years this will be commodity."

That sounds like trickle down ML research to me. I'm not convinced. But you'd kinda have to make that case, because otherwise "this is good to most extent" doesn't seem so believable. One big aspect of what industry-guided research has given people is all the burn-out, anxiety, sense of loss of agency, UI dark patterns, polarization, and dumbing down of the internet. Along some huge upsides, yes, but I wouldn't call that these are "a few very remote situations".

You have several fair points. The overall direction of course gets some incentives from industry. But there are government sponsorships & private fellowship too. ELLIS, DARPA, NSF, NIH invest several billion dollars each year to R1, CAREER, MRI, SURF programs which takes care of fledgling topics until they see more adoption. Simons Foundation e.g. similarly hosts several hundred researchers to work on CS theory.

Also Google and AWS in particular have put in a lot of money on ML/RL based solutions - on reducing electricity grid loads, Alphafold protein & drug discovery, neuroscience, precision agriculture, personalized education & even interplanetary science/astronomy. You could argue these could be glamorized CSR programs. But in net effects, they are advancing our understanding in several discipline which do not directly feed their bottomlines.

(Full disclosure again: I am not affiliated to any FAGMA or benefitted from any of these grants)

Seeing modern tech {e,in}volution, all on big of IT interests and almost zero for users and other not-so-big companies interests... I disagree.

Actual tech came from the big lab era starting from Xerox PARC, since them no real evolution was made, just improvements and new way to make people bound instead of being empowered by IT, IMVHO that's means just a thing: private-company made IT evolution is harmful for the society and then must be erased so badly that no one in the future will even think for an instance to try re-proposing it.

The solution IMO does not goes much through conferences but through universities that must be publicly founded, and ONLY founded by the public no to research "for business" but "for society", not to form "workers of the future" but "citizens of the future", doing so left a healthy business world and a healthy society.