Anyone claiming to be unbiased, rather than wearing their biases on their sleeves, is lying to you, or themselves, or they are just ignorant.
Likely some combination of all three.
By definition, news is things that are newsworthy. I.e. the most common things to tech receive coverage are the uncommon to things.
If four people get shot over the weekend in Riverdale, not news. If four people get shot over the weekend in Beverly Hills, news.
You don't even have to try to bias news for it be biased. (Now imagine if you try.)
Underreporting on violence in certain communities vs others is biased. Who determines what is uncommon vs common? Who decides the value of 4 people in Riverdale vs 4 people in Beverly Hills? Just going by “frequency of shootings” is a form of bias.
We can get within a few fractions of a percent of absolute zero but we can't sensibly agree on what "unbiased" even looks like.
You would still have to pose the right questions or risk dying in ignorance.
People's complaints here about bias is really about being manipulated successfully by parts of society working actively in their own, markedly different, interests.
Those won't just go away. Aligning interests doesn't happen by providing facts.
I realise now that my messaging with this project is off.
What would more accurately explain the purpose of this project is to reduce the effects of sensationalism and indoctrination in the news.
In other words, provide a platform for readers to make up their own opinions on news stories by filtering out the excessive positive/negative language.
Even if NewsNotFound articles are only 90% neutral, that's 90% BETTER than reading the same story from a sensationalist source.
Humans provide their sentiment about developments to further their individual interests. Other people want to be informed about those motivations. Taking that away makes news subjectively meaningless for most.
There is a minority of truth-seekers who essentially individually engage in OSINT activity (if only by consuming more than one source).
An AI "doing the thinking for them" isn't the right way though (trust is an issue, remember). You want to teach people, how to be an intelligence analyst and give them the tools to avoid the drudgery.
The goal or call it “aspiration” to serve unbiased news is admirable to me, even while my rational mind knows the aspiration is an unattainable ideal. I will give them a try. Then I can judge their sincerity and performance relative to their aspiration.
Edit: added “judge”
Who defines what is “unbiased”? What are their biases?
You cannot measure something that exists in a fiction that resides independently in each person’s mind.
Objective reality exists, but objective observers do not.
Objective observation is really hard, but amenable to systems and rules that help get closer to this ideal. I'm convinced it's possible to do far better than existing news organisations do just through approaching it with an engineering mindset.
To be even 90% unbiased is 90% better than a sensationalist source.
I'm sure we can get very close to 100% as LLMs progress and if more talented people contribute to the project.
There is no way to judge whether or not you are close to some objective view of “unbiased news”. So it is not a worthwhile pursuit.
As others have noted, what is “newsworthy” is an entirely subjective prioritization of events and information. Are four deaths in Riverside news? Are four deaths in Palm Springs? Are both? Are neither? It depends on your subjective priorities, as a consumer, and no single news organization is ever going to achieve universal, subjective, but somehow unbiased news prioritization.
Labeling anyone person or group’s prioritization of information as “truth” is a dubious endeavor. Dubious to the point of being laughable.
Back to the topic: we seem to be talking about a human being choosing between competing news sources. As that consumer, you get to define "unbiased" for yourself. Wise people have given it a lot of thought, so you might consider consulting what they said.
And you can draw the line at something being measurable to matter to you. That's your choice. I have found the things that matter most are fictions in my brain: love comes to mind.
It is also not necessary to measure to detect a distance. I love my dog, and I love my child. I cannot measure love, yet I detect a significant distance between my love for my dog and my love for my child.
Like love, "bias" has meaning even if it cannot be measured. Like love, one can detect distances between biases, even if they cannot be measured. Science (measurement), math (quantity), and logic (relations of ideas) are just as ephemeral, because they are founded upon unprovable axioms and norms.
I'd love to hear your thoughts after giving the site a try (please use the contact page on the website).
It is by no means perfect right now, but the goal is to get as close to perfect as possible.
Even if NewsNotFound articles are only 90% neutral right now, that's 90% BETTER than reading the same story from a sensationalist source.
If you read sources bias in both directions, you at least know the truth is probably somewhere within that range.
Granted that range can be quite large at times.
What would more accurately explain the purpose of this project is to reduce the effects of sensationalism and indoctrination in the news.
In other words, provide a platform for readers to make up their own opinions on news stories by filtering out the positive/negative language.
Even if NewsNotFound articles are only 90% neutral, that's 90% BETTER than reading the same story from a sensationalist source.
Also, filtering out the positive and negative language might hide the bias of the article, making it seem more authoritative and believable. Many times when I read an article, and I see the journalist making conclusions with bombastic and unbalanced language, it is helpful information toward allowing me to detect bullshit and avoid that source.
1. Information that immediately affects me
2. Information that might affect me
3. Information that doesn't affect me but I still care to know
4. Information that won't affect me
5. Information that won't affect me and I don't care to know
6. Information I don't care to know even if it affects me
Surely there must be a way to monetize information delivery. I would pay for an editorial-less stream of information that is relevant to me, and that isn't that I still want to know.
I removed all other news apps from my phone and only leave the Reuters news app installed. [1]
I never read the news anymore.
The combination of the deluge of articles about stuff I don't know anything about and them not really poking my buttons with editorialized headlines makes me just ignore it and come here more often instead.
Maybe for American news it is unbiased across conservatives / liberals, however from a non-American point of view Reuters is very VERY much biased towards US / CIA (even though it is incorporated in England).
Human communication has the aspects of content, sentiment and style. People look at style first, as they take it as an indicator for the social standing of the speaker. Sentiment is a close second, as it tells you about the attitude that speaker has towards the reported events. Content lastly is just the events themselves as they (reportedly) happened.
People find that content part hard to follow on its own, mostly because they usually don't really know the context anyway. Focusing on it as supposedly important "unbiased" "true" news is a gross misunderstanding.
Like yourself, people generally have a very incomplete idea of the world they live in. Like you, they don't seem to take much interest in it, as they view it as "not relevant to their lives". That is an absurd statement to make, if one has no clue about that part of the world to begin with, like you observed.
https://www.reuters.com/article/us-britain-media-idUSKBN1ZC2...
Makes you wonder what the as yet to be declassified top secret documents say.
The secret government financing of Reuters - as set out in the documents - amounted to 245,000 pounds ($317,838 at current exchange rates) per year before 1969 but then reduced to 100,000 pounds per year in 1969-1970 and nothing in 1972-1973.”
I don’t grasp what the article’s writer meant by “current exchange rates” and “before 1969” here, but in any event it sounds like only a few million real constant 2023 dollar equivalents, total, were involved, which is less like a secret think tank and more like travel and bureau support, which is basically what is being admitted to.
As seen recently when Fox buried the story of their defamation case.
According the so-called "tech" industry, the people setting up websites like this one, even the people financing HN, we should all care about "AI" and ChatGPT.
There really isn't much balance. The "news" from these intermediaries is weighted so heavily toward one objective. More data collection about users and more targeted advertising.
Certainly an important catgory of news is local news. What is happening in local communities. "AI" does not really fit in that category. It's just heaps of general statements about "changing the world".
What's going on in a local community is certainly news and reporting it requires people who actually live in these communities.
People in local communities should be discussing news that is relevant to them, not only "news of AI and ChatGPT" or whatever is being delivered to their screens by "tech" company middlemen (third party intermediaries). One cool thing about the internet is that it should allow people anywhere in the world to follow the news in any local community, not only the one they live in.
However, I realized that’s not really true.
I mean, of course you cannot have unbiased news, and reevaluating the definition of “news” is not going to help you.
It’s just that there is actually a very good mechanism for combatting this—and it’s called “be aware of your bias and upfront about it”. There is any other way around it.
1. Identify all clusters of power and opinion, eg. Republicans, Democrats, Chinese Communist Party, UK Labour Party, Green Party, etc.
2. Associate each cluster with news organizations that tightly align with their policies.
3. Evaluate stories - headlines in only one cluster (under reported elsewhere) represent a view. Headlines that have different takes, likewise, give you a spectrum of thought on an issue or topic.
4. Collect fine points and build a report. Bonus for providing contrasting opinions and associating them with the party/power responsible for that thinking.
I want this tool. It'd be okay if it wasn't perfect. Just getting 80% of the way there would be incredibly valuable. I'd pay for it.
I didn't think so.
You can absolutely say a newspaper (or individual columnist or editor) is pro-LGBT, pro-Israel, pro-Palestine, pro-Mormon, pro-Amish, pro-Atheist, etc. That shouldn't be controversial. Wikipedia can and does do this in a relatively neutral way.
If your classification is meant to disparage a group, then I'd see the trouble. Don't do that.
I want an up to date, well rounded view of how everyone sees the world. A system capable of getting me to see geopolitical events in other perspectives is useful, even if I ultimately choose to uphold my existing beliefs.
FWIW, I subscribe to all sorts of diverse political view subreddits and Twitter handles. Unfortunately, it's still hardly comprehensive is a lot of work to analyze and distill.
I.e. Christians (as an averaged whole) can look at the same situation as a blank slate and have a statistically significant and consistently different perspective
As can scientists. As can maybe microbiologists and industrial chemists.
The point of the clustering isn't that the tags are pejorative, but that they're predictive metadata on any source's bias.
And often times that's currently unexposed. I see a post by echelon, but only by the content of that single post (and maybe some prior HN contact) can I reconstruct his typical perspectives.
Your "to be precise" sentence states directly that what you read WILL be biased.
Furthermore, the intent of parent's bias averaging, as I understand it, is...
1) There are a finite number of major biases axes in mass media (e.g. political parties, wealthy-poor, conservative-liberal, etc.), ergo averaging these out is a helpful reduction of major biases
2) It assumes the underlying material has a bias, and seeks to counteract it. If you build a fact-based method, you leave yourself open to treating biased opinions as facts, if they're sufficiently masked
I don’t know if it is clear but I really meant it that unbiased news is not a possibility due to fundamental limitations of information theory and finiteness of individual information processing capabilities; self-awareness and bias transparency is the only way.
> helpful reduction of major biases
Only if those major biases are opposite between media.
Imagine biases as vectors pointing in arbitrary directions. Best case is when bias vector in one cluster is compensated by exactly opposite bias vector in another cluster, but how often do you expect that to happen? A more typical scenario is a vector pointing in merely a different, rather than opposite, direction. A worst-case scenario, and also common (because bias manifests itself in selection if facts to report, and most sources report on the same events), is when all bias vectors point in a similar direction.
As for averaging out, yes, the vector model was what I was using internally.
Disclosure: I'm US-based, so our politics are traditionally bipolar as a result of our election system (in contrast to Europe et al.).
I would be surprised if vectors don't cancel often though, because think what we're really talking about in a capitalist information space: popular perspectives that are profitably marketable.
What is the easiest way to find an audience? Do what your competitors are not.
So on the whole, high revenue and production cost media (tv, web) in a capitalist information space will converge into bipolar pairs on any given issue, in order to maximize market share.
In lower cost media or operations, it will more likely be a random scattering of vectors.
There's a whole lot of bias that's "baked in" with US politics / media. There's broad consensus on neoliberal capitalism, personal freedoms vs collectivism, common ground on opposing states like Russia and China.
On a few wedge issues you will average out to a common ground, but ultimately you're not eliminating bias, you're just eliminating a relatively small bias between left-wing and right-wing US and replacing it with an "overall US" bias.
As for whether averaging that out is useful...?
I'd be happy to have news from a "overall US" bias, without the right/left political spin.
Corollary: since this awareness of the bias requires self-honesty and introspection, it’s drastically more difficult with an LLM because you also need to know all about your LLM developer and operator’s accidental and intentional biases.
For example, one way in theory is to scrape all known publicly available news sites and create an article for every single detected story, but this would be very expensive.
As someone with experience in the media, what steps would you take to find these under-reported stories? Maybe the steps can be replicated with AI to increase coverage?
twitter and reddit do a pretty good job publicizing it though
But there is no such thing as a pure fact, innocent of interpretation. Behind every fact presented to the world—by a teacher, a writer, anyone—is a judgment. The judgment that has been made is that this fact is important, and that other facts, omitted, are not important.
From my own experience, I can tell you that the most important news stories are often the ones that go unreported/underreported by most news sites. Unfortunately, there are also many insidious methods used to shape public opinion, such as distraction etc. But it all starts with the decisions made by editors about WHAT YOU, as a reader, should SEE and CARE about. So if we truly want to achieve unbiased news, we need to start by reevaluating the very definition of what is news.