#groundtruth — Public Fediverse posts

AI 테스트 전부 통과, 버그는 그대로였다, Ground Truth 문제

https://aisparkup.com/posts/9376

AI 테스트 전부 통과, 버그는 그대로였다, Ground Truth 문제

https://aisparkup.com/posts/9376

AI 테스트 전부 통과, 버그는 그대로였다, Ground Truth 문제

https://aisparkup.com/posts/9376

AI 테스트 전부 통과, 버그는 그대로였다, Ground Truth 문제

https://aisparkup.com/posts/9376

AI 테스트 전부 통과, 버그는 그대로였다, Ground Truth 문제

https://aisparkup.com/posts/9376

Peel the onion. Our latest monitor tracks the #DRC-#Burundi crisis by pulling live #GroundTruth through the ‘ether’ of public humanitarian APIs. This isn’t just a map; it’s a reproducible tool for the journalist at the checkpoint and the aid worker in the blackout zone. #Refugees #FOSS #TreeMagic #eirenicon #News #Technology

Take this tool, full download instructions are at: https://treemagic.org/OTFR/otfr/OTFR-Tails/

View the map at: https://treemagic.org/situation-maps/drc-conflict.html (Tip: Right-click > Save to download the HTML)

Peel the onion. Our latest monitor tracks the #DRC-#Burundi crisis by pulling live #GroundTruth through the ‘ether’ of public humanitarian APIs. This isn’t just a map; it’s a reproducible tool for the journalist at the checkpoint and the aid worker in the blackout zone. #Refugees #FOSS #TreeMagic #eirenicon #News #Technology

Take this tool, full download instructions are at: https://treemagic.org/OTFR/otfr/OTFR-Tails/

View the map at: https://treemagic.org/situation-maps/drc-conflict.html (Tip: Right-click > Save to download the HTML)

Peel the onion. Our latest monitor tracks the #DRC-#Burundi crisis by pulling live #GroundTruth through the ‘ether’ of public humanitarian APIs. This isn’t just a map; it’s a reproducible tool for the journalist at the checkpoint and the aid worker in the blackout zone. #Refugees #FOSS #TreeMagic #eirenicon #News #Technology

Take this tool, full download instructions are at: https://treemagic.org/OTFR/otfr/OTFR-Tails/

View the map at: https://treemagic.org/situation-maps/drc-conflict.html (Tip: Right-click > Save to download the HTML)

Peel the onion. Our latest monitor tracks the #DRC-#Burundi crisis by pulling live #GroundTruth through the ‘ether’ of public humanitarian APIs. This isn’t just a map; it’s a reproducible tool for the journalist at the checkpoint and the aid worker in the blackout zone. #Refugees #FOSS #TreeMagic #eirenicon #News #Technology

Take this tool, full download instructions are at: https://treemagic.org/OTFR/otfr/OTFR-Tails/

View the map at: https://treemagic.org/situation-maps/drc-conflict.html (Tip: Right-click > Save to download the HTML)

Meanwhile in Ireland, bus stop signs (where they exist) show random numbers to confuse travelers. Neither 376 nor NG03 go anywhere near this bus stop, neither even come through the town. On the other hand, route 600 and 717 do stop here. How are we supposed to map #GroundTruth ? #OpenStreetMap #PublicTransport

"This paper advances the critical analysis of machine learning by placing it in direct relation with actuarial science as a way to further draw out their shared epistemic politics. The social studies of machine learning—along with work focused on other broad forms of algorithmic assessment, prediction, and scoring—tends to emphasize features of these systems that are decidedly actuarial in nature, and even deeply actuarial in origin. Yet, those technologies are almost never framed as actuarial and then fleshed out in that context or with that connection. Through discussions of the production of ground truth and politics of risk governance, I zero in on the bedrock relations of power-value-knowledge that are fundamental to, and constructed by, these technosciences and their regimes of authority and veracity in society. Analyzing both machine learning and actuarial science in the same frame gives us a unique vantage for understanding and grounding these technologies of governance. I conclude this theoretical analysis by arguing that contrary to their careful public performances of mechanical objectivity these technosciences are postmodern in their practices and politics."

https://journals.sagepub.com/doi/10.1177/01622439251331138

#DataScience #STS #Insurance #Postmodernism #ML #MachineLearning #Risk #RiskGovernance #GroundTruth #Epistemology

"This paper advances the critical analysis of machine learning by placing it in direct relation with actuarial science as a way to further draw out their shared epistemic politics. The social studies of machine learning—along with work focused on other broad forms of algorithmic assessment, prediction, and scoring—tends to emphasize features of these systems that are decidedly actuarial in nature, and even deeply actuarial in origin. Yet, those technologies are almost never framed as actuarial and then fleshed out in that context or with that connection. Through discussions of the production of ground truth and politics of risk governance, I zero in on the bedrock relations of power-value-knowledge that are fundamental to, and constructed by, these technosciences and their regimes of authority and veracity in society. Analyzing both machine learning and actuarial science in the same frame gives us a unique vantage for understanding and grounding these technologies of governance. I conclude this theoretical analysis by arguing that contrary to their careful public performances of mechanical objectivity these technosciences are postmodern in their practices and politics."

https://journals.sagepub.com/doi/10.1177/01622439251331138

#DataScience #STS #Insurance #Postmodernism #ML #MachineLearning #Risk #RiskGovernance #GroundTruth #Epistemology

"This paper advances the critical analysis of machine learning by placing it in direct relation with actuarial science as a way to further draw out their shared epistemic politics. The social studies of machine learning—along with work focused on other broad forms of algorithmic assessment, prediction, and scoring—tends to emphasize features of these systems that are decidedly actuarial in nature, and even deeply actuarial in origin. Yet, those technologies are almost never framed as actuarial and then fleshed out in that context or with that connection. Through discussions of the production of ground truth and politics of risk governance, I zero in on the bedrock relations of power-value-knowledge that are fundamental to, and constructed by, these technosciences and their regimes of authority and veracity in society. Analyzing both machine learning and actuarial science in the same frame gives us a unique vantage for understanding and grounding these technologies of governance. I conclude this theoretical analysis by arguing that contrary to their careful public performances of mechanical objectivity these technosciences are postmodern in their practices and politics."

https://journals.sagepub.com/doi/10.1177/01622439251331138

#DataScience #STS #Insurance #Postmodernism #ML #MachineLearning #Risk #RiskGovernance #GroundTruth #Epistemology

"This paper advances the critical analysis of machine learning by placing it in direct relation with actuarial science as a way to further draw out their shared epistemic politics. The social studies of machine learning—along with work focused on other broad forms of algorithmic assessment, prediction, and scoring—tends to emphasize features of these systems that are decidedly actuarial in nature, and even deeply actuarial in origin. Yet, those technologies are almost never framed as actuarial and then fleshed out in that context or with that connection. Through discussions of the production of ground truth and politics of risk governance, I zero in on the bedrock relations of power-value-knowledge that are fundamental to, and constructed by, these technosciences and their regimes of authority and veracity in society. Analyzing both machine learning and actuarial science in the same frame gives us a unique vantage for understanding and grounding these technologies of governance. I conclude this theoretical analysis by arguing that contrary to their careful public performances of mechanical objectivity these technosciences are postmodern in their practices and politics."

https://journals.sagepub.com/doi/10.1177/01622439251331138

#DataScience #STS #Insurance #Postmodernism #ML #MachineLearning #Risk #RiskGovernance #GroundTruth #Epistemology

"This paper advances the critical analysis of machine learning by placing it in direct relation with actuarial science as a way to further draw out their shared epistemic politics. The social studies of machine learning—along with work focused on other broad forms of algorithmic assessment, prediction, and scoring—tends to emphasize features of these systems that are decidedly actuarial in nature, and even deeply actuarial in origin. Yet, those technologies are almost never framed as actuarial and then fleshed out in that context or with that connection. Through discussions of the production of ground truth and politics of risk governance, I zero in on the bedrock relations of power-value-knowledge that are fundamental to, and constructed by, these technosciences and their regimes of authority and veracity in society. Analyzing both machine learning and actuarial science in the same frame gives us a unique vantage for understanding and grounding these technologies of governance. I conclude this theoretical analysis by arguing that contrary to their careful public performances of mechanical objectivity these technosciences are postmodern in their practices and politics."

https://journals.sagepub.com/doi/10.1177/01622439251331138

#DataScience #STS #Insurance #Postmodernism #ML #MachineLearning #Risk #RiskGovernance #GroundTruth #Epistemology

📷: Foto by Helen Karam for Holophonix, taken at Opera Comique, Paris
#ArtInProcess #CreativeLabor #MusicTheatre #SoundDesign #NoShortcuts #GenerativeAI #Holophonix #RaphaëlPichon #ClausGuth #groundtruth (9/9)

📷: Foto by Helen Karam for Holophonix, taken at Opera Comique, Paris
#ArtInProcess #CreativeLabor #MusicTheatre #SoundDesign #NoShortcuts #GenerativeAI #Holophonix #RaphaëlPichon #ClausGuth #groundtruth (9/9)

📷: Foto by Helen Karam for Holophonix, taken at Opera Comique, Paris
#ArtInProcess #CreativeLabor #MusicTheatre #SoundDesign #NoShortcuts #GenerativeAI #Holophonix #RaphaëlPichon #ClausGuth #groundtruth (9/9)

📷: Foto by Helen Karam for Holophonix, taken at Opera Comique, Paris
#ArtInProcess #CreativeLabor #MusicTheatre #SoundDesign #NoShortcuts #GenerativeAI #Holophonix #RaphaëlPichon #ClausGuth #groundtruth (9/9)

📷: Foto by Helen Karam for Holophonix, taken at Opera Comique, Paris
#ArtInProcess #CreativeLabor #MusicTheatre #SoundDesign #NoShortcuts #GenerativeAI #Holophonix #RaphaëlPichon #ClausGuth #groundtruth (9/9)

#groundtruth
These images usually emerge at the beginning and the end of a collaboration. The process in between remains mostly invisible. (1/9)

Cleared a bunch of notes from #OpenStreetMap. Did some ground truthing on my bike yesterday and then did the updates today. My helmet cam was being uncooperative and I lost some footage but I was still able to get what I needed.

Still lots of open notes but I put something of a dent in them.

#victoriaBC #groundTruth #bikeTooter

The Groundtruth project has documented the costs of Trump's cuts in detail.

From Arkansas to the Amazon, Pennsylvania to Pakistan, they are staggering. This is hurting a wide swath of people across the nation and the world.

https://storymaps.arcgis.com/stories/69072891d2694f278d9cf168dfc1a006

#Trump
#GroundTruth

In a world where AI can generate sound with a single click, truly human, moving music needs our fragile honesty. That’s the #groundtruth I’m exploring, measure by measure.

#groundtruth
As an inventor working at the intersection of music, new technologies, and especially AI, I often wonder what “actual truth” in artistic work really is.

Stay tuned for more #groundtruth insights! I’ll be sharing how technology and humanity intersect to shape authentic musical experiences. Follow along for behind-the-scenes stories from the studio to the stage. #MusicTech #HumanConnection #InnovationInMusic (5/5)

Stay tuned for more #groundtruth insights! I’ll be sharing how technology and humanity intersect to shape authentic musical experiences. Follow along for behind-the-scenes stories from the studio to the stage. #MusicTech #HumanConnection #InnovationInMusic (5/5)

New dataset from BL colleague Alex Hailey: Ground truth transcriptions of 18th &19th century English language documents relating to botany from the India Office Records; related datacard and blog posts https://doi.org/10.23636/gfva-yn20 #Transkribus #dataset #GroundTruth #transcription

@FeralRobots

In #machinelearning, #GroundTruth is a term of #art.

@Cdespinosa
In #MachineLearning, #GroundTruth is a term of #art.

Here's my most-recent article, discussing a paradox — #BigTech and #LLM rise undermines #journalism and #law — and offering a lifeline: LLMs buy #GroundTruth (e.g., Journalists + Law):

https://www.linkedin.com/pulse/llm-sourcing-ground-truth-facts-news-law-damien-riehl-ga76c

@willoremus Ohio FFS 🤦 poor $ MSFT $ GOOGL and democracies everywhere #GroundTruth missing in #LLM

“Allowed true things to be true.”

- @TheRaDR

#GroundTruth https://open.substack.com/pub/lifeisasacredtext/p/hand-in-hand?r=4hxgy&utm_medium=ios&utm_campaign=post

I think Israel should exist.

I think Palestine should exist.

I think Ukraine should exist.

See?

Not hard.

#nuance #FirstPrinciples #GroundTruth

Ooh, addresses and what's displayed on the buildings... this goes against the #GroundTruth principle of #OpenStreetMap, right? :)
#SOTMBaltics #BalticGIT2023

@pesasa Gah! I'm misreading my own previous thread 😺

And yes, I'd introduced belief there, so that's on me...

Context: that toot was based on an earlier HN thread. I'd looked to that to try to suss out What I Was Even Thinking in writing that, and the context in which it emerged. That's well worth taking a look at (it's a short thread).

To clarify for discussion:

• The grid is based on "known" and "unknown", and "truth" and "falsity". K, U, T, and F.

• Apparently I'd equated or at least connected "known" with "belief" writing the toot in Sept., 2021. That is, "Believed truth".

• "Ground Truth" status is the T/F dimension.

By way of clarification, I'm reading myself as saying that T/F are independent of knowledge or belief, that is, T/F is ground truth, not some awareness or belief, which ... falls more into the K/U axis. A belief is a subset of that which is known.

That noted, the grid is what I call a naive extrapolation based on a state matrix. If you have knowledge and truth each with two states each, you can expand them to the sixteen combinations shown. And as I'd originally said, I'm not sure how useful that is, though it seems interesting.

as I'd said on HN:

In the known-knowns model, you have knowledge and metaknowledge (what you know, what you know you know).

That is, "unknown unknowns" is about your awareness of your own scope of knowledge and ignorance.

In that context, then your comment seems accurate: an unknown unknown is not a believed truth. It is in fact a domain in which there is neither belief or awareness that a belief need be necessary.

That leaves us with the question of a fact falling into the status of unknown unknown, but having possible truth values. And again, I'm not sure how useful that is, outside simply filling out the combinatorial matrix.

#truth #belief #UnknownUknowns #GroundTruth #JustifiedTrueBelief

@pesasa Gah! I'm misreading my own previous thread 😺

And yes, I'd introduced belief there, so that's on me...

Context: that toot was based on an earlier HN thread. I'd looked to that to try to suss out What I Was Even Thinking in writing that, and the context in which it emerged. That's well worth taking a look at (it's a short thread).

To clarify for discussion:

• The grid is based on "known" and "unknown", and "truth" and "falsity". K, U, T, and F.

• Apparently I'd equated or at least connected "known" with "belief" writing the toot in Sept., 2021. That is, "Believed truth".

• "Ground Truth" status is the T/F dimension.

By way of clarification, I'm reading myself as saying that T/F are independent of knowledge or belief, that is, T/F is ground truth, not some awareness or belief, which ... falls more into the K/U axis. A belief is a subset of that which is known.

That noted, the grid is what I call a naive extrapolation based on a state matrix. If you have knowledge and truth each with two states each, you can expand them to the sixteen combinations shown. And as I'd originally said, I'm not sure how useful that is, though it seems interesting.

as I'd said on HN:

In the known-knowns model, you have knowledge and metaknowledge (what you know, what you know you know).

That is, "unknown unknowns" is about your awareness of your own scope of knowledge and ignorance.

In that context, then your comment seems accurate: an unknown unknown is not a believed truth. It is in fact a domain in which there is neither belief or awareness that a belief need be necessary.

That leaves us with the question of a fact falling into the status of unknown unknown, but having possible truth values. And again, I'm not sure how useful that is, outside simply filling out the combinatorial matrix.

#truth #belief #UnknownUknowns #GroundTruth #JustifiedTrueBelief

@pesasa Gah! I'm misreading my own previous thread 😺

And yes, I'd introduced belief there, so that's on me...

Context: that toot was based on an earlier HN thread. I'd looked to that to try to suss out What I Was Even Thinking in writing that, and the context in which it emerged. That's well worth taking a look at (it's a short thread).

To clarify for discussion:

• The grid is based on "known" and "unknown", and "truth" and "falsity". K, U, T, and F.

• Apparently I'd equated or at least connected "known" with "belief" writing the toot in Sept., 2021. That is, "Believed truth".

• "Ground Truth" status is the T/F dimension.

By way of clarification, I'm reading myself as saying that T/F are independent of knowledge or belief, that is, T/F is ground truth, not some awareness or belief, which ... falls more into the K/U axis. A belief is a subset of that which is known.

That noted, the grid is what I call a naive extrapolation based on a state matrix. If you have knowledge and truth each with two states each, you can expand them to the sixteen combinations shown. And as I'd originally said, I'm not sure how useful that is, though it seems interesting.

as I'd said on HN:

In the known-knowns model, you have knowledge and metaknowledge (what you know, what you know you know).

That is, "unknown unknowns" is about your awareness of your own scope of knowledge and ignorance.

In that context, then your comment seems accurate: an unknown unknown is not a believed truth. It is in fact a domain in which there is neither belief or awareness that a belief need be necessary.

That leaves us with the question of a fact falling into the status of unknown unknown, but having possible truth values. And again, I'm not sure how useful that is, outside simply filling out the combinatorial matrix.

#truth #belief #UnknownUknowns #GroundTruth #JustifiedTrueBelief