#medical ai

[drcardiobear]

A stething session outdoors in nature is my cardiophile dream

[ginbenci]

“Our findings suggest that LLMs perform worst for exactly the kind of patients that might need this information the most. Where inquiries are mediated by medical professionals, LLMs have an easier time pointing to reliable sources. This has substantial implications for the distributive effects of this technology on health knowledge.”

Those who already know the answers don’t need it; those who don’t can’t trust it.

What are we doing again?

[pjoshi12]

Revolutionize Healthcare With Spatial Computing

Spatial computing, encompassing AR, VR, and MR, is revolutionizing healthcare by merging digital and physical realms. It enhances patient centered care, boosts surgical precision, and transforms medical education. As this technology integrates into healthcare, understanding its potential is crucial for professionals navigating a digitally augmented future.

The Foundations of Spatial Computing in Healthcare

Spatial computing blends physical and digital worlds through AR, VR, and MR, revolutionizing healthcare enhancements.

Augmented Reality (AR)

AR overlays digital info onto the real world, aiding surgeries and diagnostics by providing real-time data. It has reduced surgical errors and improved efficiency by up to 35% in studies.

Virtual Reality (VR)

VR immerses users in virtual environments, facilitating training and simulation for medical procedures. VR-trained surgeons perform 29% faster and are 6 times less likely to make errors compared to traditionally trained counterparts.

Mixed Reality (MR)

MR combines AR and VR, enabling real-world interaction with virtual objects, enhancing collaborative medical settings. It facilitates surgical planning and improves educational outcomes through engaged learning experiences.

Spatial computing integrates into healthcare IT systems, supported by devices like Apple Vision Pro and platforms from Microsoft and Google, enhancing user experiences. Understanding its capabilities is crucial for healthcare professionals to optimize patient care and operational efficiency as its applications become more widespread.

Enhancing Surgical Precision and Safety

Spatial computing revolutionizes surgical practices, enhancing precision, safety, and patient outcomes through AR and VR integration.

Augmented Reality in Surgical Procedures

AR enhances surgical precision by overlaying real-time, 3D images of patient anatomy, reducing invasive exploratory procedures. AR-guided surgeries decrease operation duration by up to 20% and improve surgical precision, minimizing postoperative complications.

Virtual Reality for Surgical Training

VR simulations offer hands-on training without live procedure risks, especially beneficial for neurosurgery and orthopedics. VR-trained surgeons perform procedures approximately 30% faster and have error rates reduced by up to 40% compared to traditional methods.

Mixed Reality for Collaborative Surgery

MR fosters collaboration by combining VR and AR benefits, allowing real and digital elements to coexist. It aids in complex surgeries, potentially reducing operation times and enhancing outcomes through improved teamwork and planning.

Case Study: Implementing AR in Orthopedic Surgery

AR technology in orthopedic surgery achieves 98% accuracy in implant alignment, surpassing traditional methods by 8%.

The Future of Surgical Precision

Advancements like AI-enhanced spatial computing and lighter AR glasses will refine surgical precision. Integration of spatial computing promises safer procedures, improved outcomes, and enhanced healthcare delivery.

Revolutionizing Medical Education and Training

Spatial computing, notably through VR and AR, revolutionizes medical education by offering immersive, interactive simulations, enhancing learning and retention.

Virtual Reality in Medical Training

VR offers immersive, risk-free practice for medical students, leading to a 230% improvement in surgical technique performance.

According to AxiomQ, VR significantly enhances skill acquisition in medical training.

Augmented Reality for Enhanced Learning

AR overlays digital info onto real-world objects, improving retention rates by up to 90% for complex subjects like anatomy.

Studies indicate higher satisfaction and engagement with AR training compared to traditional methods.

Mixed Reality for Collaborative Learning

MR combines VR and AR for interactive group training, enhancing collaboration efficiency by up to 50%.

Participants in cardiology training with MR applications demonstrated a 40% faster learning curve and 25% fewer errors than those using traditional methods.

Broadening Horizons in Patient Care

Spatial computing, encompassing AR, VR, and MR, revolutionizes patient care by enhancing diagnostics, patient education, and therapies. It improves outcomes through immersive experiences, supported by statistics and real-life examples.

Enhanced Diagnostic Procedures

AR enhances diagnostic accuracy by overlaying digital info onto patient scans, leading to a 10% higher tumor detection rate. This accelerates diagnoses and improves treatment outcomes significantly.

Patient Education Through Virtual Reality

VR transforms patient education with immersive experiences, increasing understanding of health conditions by 30%. VR simulations illustrate disease effects comprehensibly to non-medical individuals.

Mixed Reality for Enhanced Therapeutic Interventions

MR customizes interactive environments for physical rehabilitation and mental health treatments, improving motor function recovery by 20% in stroke rehabilitation. Task-specific games and exercises in MR accelerate recovery rates.

Real-Life Example: Improving Chronic Pain Management

VR programs reduce chronic pain levels by 40% during sessions, decreasing reliance on pain medication. Immersive environments distract patients from pain, offering non-pharmacological pain management strategies.

The Future of Patient Care with Spatial Computing

AI advancements enable real-time adjustments to therapeutic programs, enhancing treatment effectiveness. Widespread spatial computing adoption supports remote patient monitoring and home-based care, expanding healthcare impact.

Transformative Diagnostic and Imaging Techniques

Spatial computing, encompassing AR, VR, and MR, revolutionizes diagnostic and imaging techniques in healthcare. These technologies offer unprecedented precision and interactivity, enhancing radiological imaging, detailed analysis, and real-time surgical navigation. For instance, AR improves accuracy in visualizing tumors, VR aids in preoperative planning, and MR reduces the need for secondary surgeries.

Future advancements will integrate spatial computing with AI for automated diagnostics, while lighter AR and VR hardware will facilitate broader adoption in clinical settings. This transformative approach sets a new standard in healthcare, advancing toward more personalized and effective patient care, with enhanced accuracy and reduced procedural times.

Operational Efficiencies and Future Prospects

Spatial computing, including AR, VR, and MR, significantly enhances operational efficiencies in healthcare. Integration into clinical workflows streamlines decision-making by providing real-time data and visual aids, reducing errors and speeding up routine tasks. Hospitals adopting AR for data integration report a 20% reduction in time spent on tasks like routine checks and data entry.

MR applications improve resource management by tracking equipment in real time, reducing idle time by up to 30% and boosting operational efficiency. Looking ahead, the integration of AI with spatial computing holds promise for even greater efficiencies, predicting patient flows and optimizing resource allocation. Virtual command centers utilizing VR and AR exemplify this potential, leading to a 40% improvement in response times to critical patient incidents.

Challenges and Ethical Considerations

Addressing the challenges of spatial computing in healthcare involves overcoming technical hurdles such as graphics fidelity and data accuracy, along with ensuring privacy and security compliance, particularly concerning patient data protection under regulations like HIPAA.

Ethical considerations surrounding patient consent and the psychological impacts of immersive treatments must be navigated carefully. Collaboration among technology developers, healthcare professionals, and regulatory bodies is essential to establish standards and best practices, fostering responsible adoption. Education and training for healthcare providers on the ethical and practical aspects of spatial computing will be crucial for its successful integration, ensuring transformative benefits without compromising patient privacy or well-being.

Concluding Thoughts: Envisioning the Future of Spatial Computing in Healthcare

Spatial computing is reshaping healthcare, improving surgical precision, medical training, and patient care. Despite its transformative potential, challenges such as technical limitations and ethical concerns need careful navigation for responsible integration of digital healthcare solutions.

Collaborative efforts are essential to address these challenges and unlock the full benefits of spatial computing. Advancements in AI integration, development of standards, and accessibility to underserved regions are key areas that require ongoing innovation and adaptation in the healthcare sector.

[aihallofshame]

Medical AI Recommends Self-Harm

Chatbot medical trial shut down after AI advises simulated patient that he should commit suicide 👨‍⚕️

[lenrosen]

Medical AI is About to Disrupt Medicine

[market-insider]

Revolutionizing Cancer Diagnosis: An In-Depth Analysis of the AI in Cancer Diagnostics

The global AI in cancer diagnostics market size is expected to reach USD 996.1 million by 2030, growing at 26.3% CAGR from 2023 to 2030, according to a new report by Grand View Research, Inc. The increasing need for lowering healthcare costs, the rising importance of big data in healthcare, improving adoption of precision medicine, and declining hardware costs are key factors driving the growth.

AI In Cancer Diagnostics Market Report Highlights

Based on component, the software solutions segment held the largest market share of 43.7% in 2022. The development of AI-based software solutions for cancer diagnostics is one of the key factors boosting segment growth

Based on cancer type, the other cancers segment emerged as the largest segment with a revenue share of 33.6% in 2022. Growing adoption of a sedentary lifestyle increased alcohol & tobacco consumption, and physical inactivity are driving the incidence of cancers such as bladder and skin cancers

Based on end-user, the hospital segment emerged as the largest end-user in the market, with a market share of 57.7% in 2022. The growing shortage of medical professionals and technological advancements in hospitals is expected to drive the segment

North America dominated the global market with a share of 56.0% in 2022. The rising adoption of healthcare IT solutions, the well-established healthcare sector, and the availability of funding for developing AI capabilities are some of the factors contributing to the growth of the market in the region

Gain deeper insights on the market and receive your free copy with TOC now @: Artificial Intelligence In Cancer Diagnostics Market Report

The increasing scope of applications of artificial intelligence (AI) in various healthcare fields, including diagnostics; the rising prevalence of cancer; and the growing shortage of public health workforce are some of the key factors anticipated to fuel the adoption of artificial intelligence (AI) in cancer diagnostics over the forecast period. In addition, the increasing applicability of AI-based tools in cancer care and the rise in venture capital investments is further driving the surge in demand for this technology.

The presence of prominent players in the market such as Microsoft, Flatiron, Therapixel, and Tempus, is anticipated to positively impact the growth. These players are adopting strategies such as acquisitions, collaborations, expansions, and new product launches to increase the reach of their products in the industry and increase the availability of their products & services in diverse geographical areas. For instance, in December 2021, Microsoft announced a partnership with CVS Health to develop innovative solutions for patients to improve their health while empowering healthcare professionals with tools to better service patients.

Furthermore, the rising government support in the form of funding and initiatives for the development of healthcare infrastructure is anticipated to drive the demand for technologically advanced and cost-efficient devices over the forecast period.

[reasonsforhope]

I'm worried about the rising rate of young adults getting cancer.

For what it's worth, we've actually made a shocking amount of progress against cancer - especially the most common cancers like breast cancer, and especially in the past 30 years.

Cancer rates have been falling, often dramatically (x, x, x, x, x, x). One of the best examples it that breast cancer deaths in the United States dropped 58% between 1975 and 2019 (x).

Right now, we're at the beginning of an absolute revolution in cancer care that promises to increase survival rates even further. This revolution has been going on to a lesser degree since the first human genome was successfully sequenced in the early 2000s (and in fact, the first gapless sequencing of a human genome was finally finished just two years ago, in 2022), and to a greater extent since CRISPR DNA-editing technology was first successfully tested in 2013, and since medical digitzation/digital communication and vaccination were massively spurred ahead in 2020, by the COVID pandemic (x, x).

Right now, the results of this revolution are only beginning to trickle out into actual treatments. But I guarantee you, in the next one to three decades, the way we fight cancer will be massively transformed.

We're talking personalized genome sequencing for each person with cancer - not just for early and better detection, but even to figure out what types of treatments will work best. (x, x, x, x)

We're talking using CRISPR-based DNA editing to literally cut cancer-causing mutations out of your DNA, to edit the genes of immune cells to better detect and kill cancer cells, and to kill cancer-causing viruses. (x, x, x, x)

We're talking using CRISPR-based screening to figure out how chemotherapy resistance works, so that we can overcome it - and even weaponize it. (x, x)

We're talking using CRISPR to edit immune cells so that they recognize and target the mutations of a single individual's specific tumor. (x)

We're talking new types of testing that can predict if cancer will return years before it shows up on scans. (x)

We're talking using (non-generative) AI to massively increase the accuracy and earliness of cancer detection - which by the way is already starting to happen, there are several AI-based systems that detect cancer earlier and more accurately than doctors do. (x, x, x, x, x, x)

Also, the more we transition to a green, sustainable, and ethical future, the fewer cancer-causing substances will be in the environment (fossil fuels, oil drilling, and mining are massive sources of carcinogens at every point in the process).

Cancer is awful. That is a massive understatement. But the fight against cancer is one where there are so many reasons for hope.

[godbirdart]

i've been so tired of google's new legal liability bot sitting on top of the existing highlighted result, taking up page space and either parroting exactly what the highlighted result said or offering completely unrelated or incorrect results, that i actually cheered when this came up:

"oh but AI is experimental -"

the bot told people to eat glue on pizza. you can talk yourself blue in the face about the bot's learning curve and how "it'll be improved with time", but maybe a bot being touted as the latest and greatest in scouring the internet for accurate information should not come with a permanent glaring disclaimer of "it's still learning / results may not be accurate!" as the generative AI ouroboros continues to keep on chewing.

[zuzsenpai]

I feel like people have been warning about this and I completely ignored it. Deep sigh as I force myself to remember to add “-ai” at the end of every fucking search now

(Is there an extension that turns this off??)

[thegodemperorsmycopilot]

Sister Elysia, Hospitaler

A friend's character from our group's Wrath & Glory campaign.

[mostlysignssomeportents]

Privacy first

The internet is embroiled in a vicious polycrisis: child safety, surveillance, discrimination, disinformation, polarization, monopoly, journalism collapse – not only have we failed to agree on what to do about these, there's not even a consensus that all of these are problems.

But in a new whitepaper, my EFF colleagues Corynne McSherry, Mario Trujillo, Cindy Cohn and Thorin Klosowski advance an exciting proposal that slices cleanly through this Gordian knot, which they call "Privacy First":

https://www.eff.org/wp/privacy-first-better-way-address-online-harms

Here's the "Privacy First" pitch: whatever is going on with all of the problems of the internet, all of these problems are made worse by commercial surveillance.

Worried your kid is being made miserable through targeted ads? No surveillance, no targeting.

Worried your uncle was turned into a Qanon by targeted disinformation? No surveillance, no targeting. Worried that racialized people are being targeted for discriminatory hiring or lending by algorithms? No surveillance, no targeting.

Worried that nation-state actors are exploiting surveillance data to attack elections, politicians, or civil servants? No surveillance, no surveillance data.

Worried that AI is being trained on your personal data? No surveillance, no training data.

Worried that the news is being killed by monopolists who exploit the advantage conferred by surveillance ads to cream 51% off every ad-dollar? No surveillance, no surveillance ads.

Worried that social media giants maintain their monopolies by filling up commercial moats with surveillance data? No surveillance, no surveillance moat.

The fact that commercial surveillance hurts so many groups of people in so many ways is terrible, of course, but it's also an amazing opportunity. Thus far, the individual constituencies for, say, saving the news or protecting kids have not been sufficient to change the way these big platforms work. But when you add up all the groups whose most urgent cause would be significantly improved by comprehensive federal privacy law, vigorously enforced, you get an unstoppable coalition.

America is decades behind on privacy. The last really big, broadly applicable privacy law we passed was a law banning video-store clerks from leaking your porn-rental habits to the press (Congress was worried about their own rental histories after a Supreme Court nominee's movie habits were published in the Washington City Paper):

https://en.wikipedia.org/wiki/Video_Privacy_Protection_Act

In the decades since, we've gotten laws that poke around the edges of privacy, like HIPAA (for health) and COPPA (data on under-13s). Both laws are riddled with loopholes and neither is vigorously enforced:

https://pluralistic.net/2023/04/09/how-to-make-a-child-safe-tiktok/

Privacy First starts with the idea of passing a fit-for-purpose, 21st century privacy law with real enforcement teeth (a private right of action, which lets contingency lawyers sue on your behalf for a share of the winnings):

https://www.eff.org/deeplinks/2022/07/americans-deserve-more-current-american-data-privacy-protection-act

Here's what should be in that law:

A ban on surveillance advertising:

https://www.eff.org/deeplinks/2022/03/ban-online-behavioral-advertising

Data minimization: a prohibition on collecting or processing your data beyond what is strictly necessary to deliver the service you're seeking.

Strong opt-in: None of the consent theater click-throughs we suffer through today. If you don't give informed, voluntary, specific opt-in consent, the service can't collect your data. Ignoring a cookie click-through is not consent, so you can just bypass popups and know you won't be spied on.

No preemption. The commercial surveillance industry hates strong state privacy laws like the Illinois biometrics law, and they are hoping that a federal law will pre-empt all those state laws. Federal privacy law should be the floor on privacy nationwide – not the ceiling:

https://www.eff.org/deeplinks/2022/07/federal-preemption-state-privacy-law-hurts-everyone

No arbitration. Your right to sue for violations of your privacy shouldn't be waivable in a clickthrough agreement:

https://www.eff.org/deeplinks/2022/04/stop-forced-arbitration-data-privacy-legislation

No "pay for privacy." Privacy is not a luxury good. Everyone deserves privacy, and the people who can least afford to buy private alternatives are most vulnerable to privacy abuses:

https://www.eff.org/deeplinks/2020/10/why-getting-paid-your-data-bad-deal

No tricks. Getting "consent" with confusing UIs and tiny fine print doesn't count:

https://www.eff.org/deeplinks/2019/02/designing-welcome-mats-invite-user-privacy-0

A Privacy First approach doesn't merely help all the people harmed by surveillance, it also prevents the collateral damage that today's leading proposals create. For example, laws requiring services to force their users to prove their age ("to protect the kids") are a privacy nightmare. They're also unconstitutional and keep getting struck down.

A better way to improve the kid safety of the internet is to ban surveillance. A surveillance ban doesn't have the foreseeable abuses of a law like KOSA (the Kids Online Safety Act), like bans on information about trans healthcare, medication abortions, or banned books:

https://www.eff.org/deeplinks/2023/05/kids-online-safety-act-still-huge-danger-our-rights-online

When it comes to the news, banning surveillance advertising would pave the way for a shift to contextual ads (ads based on what you're looking at, not who you are). That switch would change the balance of power between news organizations and tech platforms – no media company will ever know as much about their readers as Google or Facebook do, but no tech company will ever know as much about a news outlet's content as the publisher does:

https://www.eff.org/deeplinks/2023/05/save-news-we-must-ban-surveillance-advertising

This is a much better approach than the profit-sharing arrangements that are being trialed in Australia, Canada and France (these are sometimes called "News Bargaining Codes" or "Link Taxes"). Funding the news by guaranteeing it a share of Big Tech's profits makes the news into partisans for that profit – not the Big Tech watchdogs we need them to be. When Torstar, Canada's largest news publisher, struck a profit-sharing deal with Google, they killed their longrunning, excellent investigative "Defanging Big Tech" series.

A privacy law would also protect access to healthcare, especially in the post-Roe era, when Big Tech surveillance data is being used to target people who visit abortion clinics or secure medication abortions. It would end the practice of employers forcing workers to wear health-monitoring gadget. This is characterized as a "voluntary" way to get a "discount" on health insurance – but in practice, it's a way of punishing workers who refuse to let their bosses know about their sleep, fertility, and movements.

A privacy law would protect marginalized people from all kinds of digital discrimination, from unfair hiring to unfair lending to unfair renting. The commercial surveillance industry shovels endless quantities of our personal information into the furnaces that fuel these practices. A privacy law shuts off the fuel supply:

https://www.eff.org/deeplinks/2023/04/digital-privacy-legislation-civil-rights-legislation

There are plenty of ways that AI will make our lives worse, but copyright won't fix it. For issues of labor exploitation (especially by creative workers), the answer lies in labor law:

https://pluralistic.net/2023/10/01/how-the-writers-guild-sunk-ais-ship/

And for many of AI's other harms, a muscular privacy law would starve AI of some of its most potentially toxic training data:

https://www.businessinsider.com/tech-updated-terms-to-use-customer-data-to-train-ai-2023-9

Meanwhile, if you're worried about foreign governments targeting Americans – officials, military, or just plain folks – a privacy law would cut off one of their most prolific and damaging source of information. All those lawmakers trying to ban Tiktok because it's a surveillance tool? What about banning surveillance, instead?

Monopolies and surveillance go together like peanut butter and chocolate. Some of the biggest tech empires were built on mountains of nonconsensually harvested private data – and they use that data to defend their monopolies. Legal privacy guarantees are a necessary precursor to data portability and interoperability:

https://www.eff.org/wp/interoperability-and-privacy

Once we are guaranteed a right to privacy, lawmakers and regulators can order tech giants to tear down their walled gardens, rather than relying on tech companies to (selectively) defend our privacy:

https://pluralistic.net/2022/11/14/luxury-surveillance/#liar-liar

The point here isn't that privacy fixes all the internet's woes. The policy is "privacy first," not "just privacy." When it comes to making a new, good internet, there's plenty of room for labor law, civil rights legislation, antitrust, and other legal regimes. But privacy has the biggest constituency, gets us the most bang for the buck, and has the fewest harmful side-effects. It's a policy we can all agree on, even if we don't agree on much else. It's a coalition in potentia that would be unstoppable in reality. Privacy first! Then – everything else!

If you'd like an essay-formatted version of this post to read or share, here's a link to it on pluralistic.net, my surveillance-free, ad-free, tracker-free blog:

https://pluralistic.net/2023/12/06/privacy-first/#but-not-just-privacy

Image: Cryteria (modified) https://commons.wikimedia.org/wiki/File:HAL9000.svg

CC BY 3.0 https://creativecommons.org/licenses/by/3.0/deed.en

[hazyaltcare]

Typing Quirk Suggestions for a Robot kin

I hope it gives you a wonderful uptime! :3

Mod Vintage (⭐)

Letter replacements:

Replace "O" with zeroes "0"

Replace "i" or "L" with ones "1"

Replace "one" with "1", including "one" sounds like "any1", or "we 1 = we won" (the past tense of "win")

Replace "zero" with "0"

Frankly, you can just replace all sorts of letters with numbers, such as

R = 12

N = 17

B = 8

A = 4

E = 3

etc.

or maybe make all "A"s and "i"s capitalized, cause "A.I." (artificial intelligence

Prefixes and Suffixes:

Get inspired by programming languages!

Begin your text with "//" like a comment on C++

If you prefer other languages comment tags, you can use "< !--your text-- >"

Or maybe begin it with " int main () { std::cout << "your text"" and end with "return 0; }" like C++ too

Greet people with the classic "Hello world!"

Or greet people with "beep boop!" honestly, I have no idea where this comes from, but it's cute.

Or write down html stuff, like sandwiching your italicized text with "< em> "

The possibilities are endless!

Robot Lingo:

(under the cut because there's a LOT! maybe terabytes! ...just kidding >;3c)

.

some of these are from the machinesoul.net robot server! (not sponsored) (we're not in there anymore, but we saw the robot lingo shared there when we were)

Fronting = logged in, connected

Not fronting = logged out, disconnected

Conscious = activated

Dormant = deactivated

Blurry = no signal

Upset, angry = hacked

Small = bits, bytes

Bite = byte

Huge = gigabytes, terabytes, etc.

Your intake of food, medicine, etc. = input

Your artwork, cooking, handiwork, handwriting, etc. = output

Body = chassis, unit

Brain = CPU, processor

Mind = program, code

Imagination = simulation

Purpose = directive

Nerves = wires

Skin = plating

Organs = (function) units

Limbs = actuators

Eyes = ocular sensors

Glasses = HUD (head's up display)

Hair = wires

Ears = antennae, audio sensors

Nose = olfactory sensors

Heart = core

Liver = detoxification unit

Circulatory system = circuits

Voice = speaker, voice module, voice box

Mouth = face port

Name = designation

Sleep = sleep mode, low power mode, charging

Eat = fuel, batteries

Energy = batteries

Tired = low on batteries

Translate = compile

Memory = data, database

Bed = recharge pod/charger

Dreaming = simulation

Birthday = day of manufacture

Talking = communicating

Thinking = processing

Transitioning = modifying your chassis

Depression = downtime

Joy = uptime

Trash = scrap metal

Fresh/Clean = polished

Keysmashing = random 1s and 0s

Self-care = system maintenance

Going to the doctor = trip to the mechanic

Group = network

Anyone = anybot

[crewtawn]

If you wanna use any of my art pleeease credit me pleaseeee...

[bibbysstuff]

What would happened if we get sick? What would kinito do?

nurse you back to health of course!

[gayestcowboy]

one of the reasons i hate generative AI is that i have a chronic injury that makes me unable to write by hand for longer than a few sentences and therefore i need a keyboard in order to write essays for classes, and i’m a bit worried that professors won’t allow me to type essays as a result of potential AI use, even though i have a perfectly valid medical reason to need a keyboard. i’ve seen a few posts online saying that the only way to prevent students from relying on AI is to make them write by hand, and while i understand the sentiment and don’t even necessarily disagree with the general point, the matter of accessibility still needs to be addressed somehow, and it’s just a bit frustrating on a personal level as someone who has had to fight with teachers and professors in order for my needs to be met even before the era of chatgpt