#Role of AI Automation

[atliq-ai-technologies]

The Role of AI Automation in the Future of Banking and Financial Services

By the next decade this time, we will be living in a world where your financial decisions are guided by algorithms that learn and adapt in real-time, ensuring personalized service at every touchpoint. This is the promise of AI in banking and finance, where innovation meets necessity in an industry ripe for disruption. Recent studies predict that AI applications could potentially save banks $447 Billion by 2026, primarily through process automation and enhanced operational efficiency. This isn’t just about streamlining tasks; it’s about unleashing the true potential of data to predict customer needs, mitigate risks, and drive strategic growth. 

Imagine chatbots that resolve queries instantly, virtual assistants that manage portfolios with precision, and predictive analytics that foresee market trends before they unfold. As we navigate this transformative landscape, the future of banking isn’t just about embracing technology—it’s about harnessing it to foster deeper connections with customers and drive sustainable growth. Join us as we explore how AI in banking is reshaping the industry, propelling us toward a future where innovation and financial services converge seamlessly.

Definition and Scope of AI in Banking

Artificial intelligence in banking refers to the application of advanced algorithms and machine learning techniques to automate and enhance various banking processes. These technologies analyze vast amounts of data to derive insights, make predictions, and optimize operations with minimal human intervention.

AI’s scope in banking extends across multiple functions, from front-end customer interactions to back-office operations. It powers everything from customer service automation to fraud detection and risk management, fundamentally transforming how banks deliver services and interact with their clientele.

Personalized Customer Interactions: Enhancing Engagement through AI

One of the most profound impacts of AI in banking is its ability to deliver highly personalized customer experiences. By analyzing customer data in real-time, AI algorithms can anticipate individual needs and preferences, allowing banks to tailor their services accordingly. For instance, AI can suggest personalized investment options based on a customer’s financial goals and risk tolerance, or offer customized mortgage solutions based on real-time market conditions and personal financial histories.

This level of personalization not only enhances customer satisfaction but also strengthens customer loyalty and retention. According to a report by Epsilon, 80% of consumers are more likely to do business with a company that offers personalized experiences. AI’s transformative impact isn’t confined to banking alone; it’s also reshaping the insurance industry by automating claims processing, enhancing underwriting accuracy, and improving customer engagement through personalized policy recommendations and proactive risk management solutions.

AI and Data Analytics: Enhancing Decision-Making

In the dynamic realm of banking and financial services, the marriage of artificial intelligence (AI) and data analytics is revolutionizing decision-making processes. This section explores how AI processes large volumes of data (Big Data Utilization), enhances risk assessment and fraud detection through predictive analytics, and influences financial markets via algorithmic trading.

Big Data Utilization: How AI Processes Large Volumes of Data

AI’s capability to process and analyze massive datasets—often referred to as Big Data—is reshaping how financial institutions derive insights and make informed decisions. By leveraging machine learning algorithms, AI sifts through intricate financial data in real-time, uncovering patterns, trends, and correlations that human analysts might overlook. This enables banks to optimize lending practices, personalize customer offerings, and mitigate risks more effectively.

Predictive Analytics: Improving Risk Assessment and Fraud Detection

Predictive analytics powered by AI represents a significant leap forward in risk management for financial institutions. AI algorithms can assess historical data and current market conditions to forecast future trends and potential risks with unprecedented accuracy. This proactive approach not only enhances risk assessment models but also strengthens fraud detection capabilities by identifying anomalous patterns indicative of fraudulent activities before they escalate.

For example, banks utilize AI-driven predictive models to detect unusual transaction patterns, flagging potentially fraudulent activities in real-time and minimizing financial losses for both customers and institutions.

Algorithmic Trading: Impact of AI on Financial Markets

AI’s influence extends beyond risk management to actively shaping financial markets through algorithmic trading. AI-driven algorithms execute trades based on predefined parameters, such as market trends, price fluctuations, and economic indicators, at speeds and frequencies far exceeding human capabilities. This automation enhances market liquidity, reduces trading costs, and optimizes investment strategies for institutions and individual investors alike. High-frequency trading (HFT), a subset of algorithmic trading facilitated by AI, exemplifies this transformation by executing thousands of trades per second, responding swiftly to market changes and arbitrage opportunities.

AI and data analytics are not merely enhancing decision-making in banking and financial services; they are revolutionizing it. By harnessing the power of AI to process Big Data, refine predictive analytics, and drive algorithmic trading, financial institutions are poised to navigate complexities with agility and precision, paving the way for a more efficient, resilient, and responsive financial ecosystem. As AI technologies continue to evolve, their impact on decision-making processes is set to deepen, ushering in a new era of innovation and opportunity in the global financial landscape.

Challenges and Considerations in AI Adoption in Banking

As artificial intelligence (AI) continues to redefine banking operations, it brings forth a host of challenges and considerations that institutions must navigate to harness its full potential responsibly.  

Ethical Concerns: AI Bias and Privacy Issues- AI in banking introduces ethical challenges, such as biases in decision-making and concerns over data privacy. Ensuring transparency, fairness, and accountability in AI algorithms is crucial to building trust with customers and mitigating risks.

Workforce Implications: Impact on Jobs in Banking- While AI enhances efficiency and decision-making, it also raises concerns about job displacement. Banks should invest in reskilling programs to empower employees for new roles requiring advanced technological skills, thereby turning AI into an opportunity for innovation rather than a threat.

Security Risks: Addressing Cybersecurity Challenges- AI adoption in banking requires robust cybersecurity measures to protect sensitive data from threats like data breaches and malicious attacks. Implementing encryption, AI-powered threat detection, and compliance with data protection regulations are essential for safeguarding customer information and mitigating legal risks.

The Future Outlook: Shaping Tomorrow’s Banking Landscape

As we look ahead, the future of banking is set to be defined by transformative trends at the intersection of technology and finance. Looking forward, embracing these trends will not only drive competitive advantage but also pave the way for a more inclusive, resilient, and customer-centric banking ecosystem. By leveraging AI, blockchain, and navigating regulatory landscapes effectively, financial institutions can position themselves at the forefront of innovation in the digital era.

AI Applications in Fintech Startups: Fintech startups are at the forefront of integrating AI to revolutionize financial services. From automated investment advisors to AI-driven lending platforms, these innovations are reshaping customer experiences and operational efficiencies across the industry.

Integration with Blockchain: Blockchain technology promises secure and transparent transactions, making it a natural fit for enhancing banking operations. As banks explore blockchain’s potential for decentralized finance (DeFi) and digital currencies, collaborations between AI and blockchain could unlock new levels of efficiency and trust in financial transactions.

Adapting to Regulatory Changes: Amidst rapid technological advancements, regulatory frameworks must evolve to ensure consumer protection and system stability. Adapting to changes in data privacy laws, cybersecurity standards, and fintech regulations will be pivotal in fostering innovation while maintaining regulatory compliance.

The future of banking and financial services is poised for unparalleled transformation, driven by the integration of artificial intelligence (AI) and automation. As AI continues to permeate every facet of banking operations—from customer interactions to data analytics and risk management—it heralds a new era of efficiency, innovation, and personalized service.

AI in banking isn’t just about leveraging technology; it’s about reimagining how financial institutions operate and deliver value to customers. By harnessing AI’s predictive capabilities, banks can anticipate customer needs, optimize decision-making processes, and mitigate risks with unprecedented accuracy.

Looking ahead, the synergy between AI and banking holds immense promise. Fintech startups are pioneering AI applications that redefine financial services, while the integration of blockchain technology offers new possibilities for secure and transparent transactions. However, navigating ethical considerations, addressing workforce implications, and fortifying cybersecurity measures remain critical challenges on this transformative journey.

As the regulatory landscape evolves, financial institutions must adapt to ensure compliance while fostering innovation. Embracing AI’s potential to enhance operational efficiency and customer experiences will be crucial in staying ahead in a competitive market.

AI’s role in banking and financial services isn’t merely about automation; it’s about shaping a future where technology empowers institutions to meet evolving customer expectations and navigate complex global challenges. By embracing AI in banking, we embark on a journey toward a more connected, efficient, and resilient financial ecosystem, poised to unlock new opportunities and drive sustainable growth in the digital age.

Check out the Original Article

[public-cloud-computing]

Dive into the world where human intuition seamlessly integrates with AI brilliance in web development. Elevate your online presence with the perfect fusion of creativity and technology.

[vipschoolbaddi]

Role of AI in Modern Education

Artificial intelligence is transforming how students learn and teachers teach by offering personalised learning paths, AI-powered tutoring, automated grading and feedback, and smart content creation. By analysing individual strengths and weaknesses, AI systems tailor lessons and exercises to each learner’s pace, while chatbots and virtual tutors provide instant help on difficult concepts. Automated assessment tools not only ensure fair, unbiased grading but also deliver immediate feedback, allowing students to quickly identify and correct mistakes.

Beyond enhancing pedagogy, AI improves accessibility through speech-to-text, translation models, and centralised digital resources, making education more inclusive for learners with disabilities or language barriers. Although the benefits are clear, successful implementation of the role of AI in education still requires careful attention to data privacy, maintaining human interaction, and preventing over-reliance on technology.

[tejkohli25]

Future Jobs That AI Will Impact

Artificial Intelligence (AI) is reshaping the workforce, altering how tasks are performed, and redefining job roles across multiple industries. While some fear job displacement, AI is also creating new roles and enhancing existing ones. Understanding which jobs AI will impact—and how—is essential for career planning, education, and workforce development.

For expert insights into the balance between AI innovation and broader technological advancement, check out this article.

Industries Where AI Will Have the Greatest Impact

1. Healthcare

AI is revolutionizing diagnostics, robotic surgeries, and patient monitoring.

Jobs like radiologists, medical coders, and administrative staff will see automation in repetitive tasks.

At the same time, roles for AI specialists in healthtech and human-centered care positions will grow.

2. Finance & Banking

AI is already transforming fraud detection, risk assessment, and algorithmic trading.

Jobs in manual auditing, data entry, and basic customer service may decline.

Conversely, the demand for data analysts, cybersecurity experts, and AI compliance officers is increasing.

3. Manufacturing & Logistics

AI-driven automation is reshaping assembly lines, inventory tracking, and supply chain logistics.

Jobs involving routine manual tasks are vulnerable to automation.

Opportunities will emerge in robotics engineering, systems maintenance, and logistics AI management.

4. Retail & E-commerce

AI tools are optimizing inventory management, customer behavior tracking, and personalized shopping.

Traditional cashier and in-store support jobs may decrease.

Growth areas include e-commerce strategists, AI product recommendation specialists, and UX designers.

5. Media & Creative Industries

AI can generate text, music, videos, and artwork using platforms like GPT-4 and DALL·E.

While repetitive content creation may be automated, creative direction, storytelling, and cultural nuance still require human input.

Jobs in AI-assisted design and creative consultancy will expand.

Emerging Job Roles Driven by AI

AI Ethicists & Policy Advisors: Professionals who guide ethical and legal AI deployment.

Machine Learning Engineers & Data Scientists: Developers who build and refine intelligent systems.

Human-AI Interaction Designers: Experts ensuring AI tools are intuitive and user-friendly.

AI Trainers: People who help train models with high-quality, diverse datasets.

Cybersecurity Specialists: As AI grows, so does the need for protection against cyber threats.

Skills Needed for the AI Future

Technical Skills: Python, data science, machine learning, and automation platforms.

Soft Skills: Adaptability, critical thinking, and emotional intelligence.

Interdisciplinary Knowledge: Combining AI expertise with healthcare, finance, or law creates niche opportunities.

Tej Kohli’s Perspective on AI & Future Employment

Tech investor Tej Kohli has emphasized that while AI will transform the workforce, it will also create jobs that didn’t exist before. According to him:

AI should complement, not replace, human roles, especially in ethics, leadership, and creative thinking.

Future economies must invest in AI upskilling, vocational training, and inclusive tech education.

A balanced approach to AI deployment and regulation is essential to protect jobs and stimulate innovation.

Conclusion

AI is reshaping the job market—not just eliminating roles but creating new opportunities for growth and specialization. By embracing continuous learning and adapting to technological change, today’s workforce can prepare for the careers of tomorrow. As leaders like Tej Kohli remind us, the future of work lies in collaboration between human talent and intelligent systems.

[xlnctechnologies]

Generative AI Takes Center Stage: Why Nontechnical Roles Are Leading the Charge

Recent trends highlight a fascinating shift in the adoption of generative AI across various job categories. A McKinsey AI report reveals that 88% of AI adoption comes from nontechnical job roles, far surpassing the 12% adoption rate among traditional technical roles. This statistic underscores a more inclusive AI adoption, transcending industries and job types to drive AI-driven efficiency and workplace productivity.

Nontechnical Roles Lead the Way

Nontechnical jobs, such as administrators, educators, HR workers, nurses, and salespeople, are embracing generative AI tools as a critical part of their work. These professionals are leveraging AI solutions for task automation to reduce workloads and streamline workflows.

For example:

Educators use generative AI to prepare lesson plans and assessments, showcasing AI adoption in education.

HR workers automate candidate screening and create personalized employee engagement strategies using AI-powered content creation.

Healthcare workers rely on AI solutions to generate reports or simplify documentation tasks, highlighting AI for healthcare workers.

This widespread adoption among nontechnical professionals demonstrates the versatility of AI technologies in boosting efficiency, simplifying workflows, and enabling innovation.

Technical Roles: A Slower, Specialized Uptake

On the other hand, technical roles—such as developers, engineers, and data scientists—account for only 12% of AI adoption. While adoption is slower, its application is often more specialized, focusing on coding assistance, debugging, data analysis, and developing AI-driven tools.

Interestingly, only 2% of generative AI users are in roles bridging technical expertise and AI applications, such as data analysts, machine learning specialists, and researchers. This highlights the niche uptake of AI solutions among technical roles.

Why Nontechnical Roles Dominate AI Use

The rapid adoption of generative AI for nontechnical roles is driven by the accessibility of tools requiring minimal technical expertise. Platforms like OpenAI's ChatGPT, Google Bard, and Microsoft Copilot empower users to automate tasks, generate creative content, and simplify decision-making. These AI-powered solutions enable nontechnical job efficiency without needing advanced coding or technical knowledge, emphasizing the democratization of AI.

The Broader Implications

This data signals a paradigm shift in how businesses approach workforce productivity. Generative AI tools are no longer confined to technical specialists—it’s becoming an essential solution for a diverse range of professionals, bridging the gap between innovation and practicality.

Organizations must prioritize AI workforce training and upskilling to unlock the full potential of AI adoption across all job functions. Integrating AI technologies for task automation and content creation will enable companies to drive AI-driven innovation and remain competitive. XLNC Technologies provides end-to-end AI training and implementation strategies to help businesses maximize AI’s potential and foster a future-ready workforce.

Conclusion

As generative AI reshapes industries, its adoption among nontechnical roles highlights its transformative impact. The future of work will rely heavily on democratized AI technologies, where everyone, regardless of job type, can harness AI to amplify productivity and creativity.

For companies, this presents an opportunity to integrate AI thoughtfully, ensuring accessibility and fostering AI innovation across the board. By empowering non-technical professionals with the right tools, organizations can embrace next-gen AI adoption strategies and achieve AI-driven efficiency. XLNC Technologies continues to lead the charge in providing intelligent automation solutions, helping businesses stay ahead in the evolving AI landscape.

Source: Mckinsey & Company

[jatanshahskill]

Jatan Shah Reviews | AI in Managerial Roles

Managers are at the center of decision making and AI tools are supporting them in big ways. The likes of Power BI and Tableau, as flagged out by Jatan Shah, help managers analyze extremely complex data sets and visualize trends for facilitating strategic planning.

[suvitfintechprivatelimited]

AI in Accounting: What to Trust, What to Question

Artificial Intelligence (AI) is reshaping the accounting landscape, offering tools that promise speed, accuracy, and automation.

Accountants are increasingly using AI for communication (59%), task automation (36%), and research (31%).

Nevertheless, the growing reliance on AI also raises concerns about reliability and ethical implications.

The question is: What can accountants trust when using AI, and where should they tread cautiously?

AI excels at automating repetitive tasks like data entry and invoice matching, freeing up time for strategic activities. It can also process complex datasets quickly, improving decision-making.

Yet, its limitations—such as potential biases and dependency on quality data—demand oversight.

This is where tools like Suvit come into play.

By combining AI capabilities with human validation, Suvit enables accountants to streamline workflows while maintaining control.

It automates manual processes, ensures compliance, and empowers teams with actionable insights.

AI in accounting isn’t about replacing humans; it’s about working smarter.

The key is knowing when to rely on AI and when human expertise is irreplaceable.

To find out that read the detailed version here!

[roseband]

i wanna fling someone off a roof cause all this escalation from michael's parents was "what will the extended family think"

and now that it's just a week and a half out from the wedding and they have relatives asking them "oh a western style wedding how unique" they're acting NORMAL again are you kidding me are you FUCKING KIDDING ME?????????

so we had to deal w/ 18 months of actually demented behavior for WHAT??????? what was this all for?????? we had to book this out 18 months in advance to not have to spend an extra 10k, but was 10k usd worth this stupidity

"oh if you work it looks bad", "actually wait... now that people know where u work they respect us" UH DUH??? DUH???????? DUH??????? are you fucking kidding me duhhhh???? duh? you could have avoided the whole ass "it looks poor for our dil to work" shitfit, and a few dozen schemes to get me to quit, if you had listened to that... i work at [redacted] corporate on the art/product development team and not at the [redacted] store.....and hadn't told family i was refusing to quit my job at the [redacted] /store/.... FOR FUCKS SAKE i had a ft art job that paid well......literally before i graduated? i had it lined up before i graduated, other than 6 months during lockdowns i've worked in art since 2 days before my graduation date

can i bite people??????????? i really want to start biting? we won't get an apology out of these freaks but umm WHAT THE FUCK?

"what will the relatives think" well acshually... the relatives are like "uhmmm my daughter wants to go to school for animation or graphic design can you tell her what you did to actually get work?"

[routeget]

The Impact of Hyperautomation on the Workforce, Job Roles, and Skills for Future Employment

Hyperautomation, a term referring to the use of advanced technologies such as artificial intelligence (AI), machine learning (ML), robotic process automation (RPA), and other digital tools to automate complex tasks, is reshaping industries across the globe. This paper explores the impact of hyperautomation on the workforce, job roles, and the skills required for future employment. The study…

[txttletale]

I’ve changed most of my views on AI bc of your posts, but do you have any thoughts on/remedies for people losing their jobs to AI? Or is it a “people are gonna lose their jobs one way or another, it’s not actually AI’s fault” kind of deal…? Sorry if you’ve already talked about this before

there's somethign that riley quinn from the trashfuture podcast keeps saying -- "if your job can be replaced by AI, it was already being done by AI". which is to say, that jobs most at risk from AI replacement are ones that were borderline automated anyway. like, i say this as someone who used to write, not for the website buzzfeed itself, but buzzfeed-adjacent Slop Content for money -- i was already just the middlewoman between the SEO optimization algorithm and the google search algorithm. those jobs vanishing primarily means that middlewoman role has been cut, computers can tell other computers to write for computers.

& similarly this is why i keep saying that, e.g. stock photographers are at risk from this, because the ideal use case for generative AI content is stuff where the actual content or quality of the image/text doesn't matter, all that matters is its presence. and yknow, living in a world where many people's livelihoods were dependent on writing and art that is fully replacable by inane computer drivel is itself indicative of something about culture under capitalism, right?

& to some degree, like i'm always saying, the immiseration of workers by advancement in technology is a universal feature of capitalism -- i recommend you read wage labour & capital to see how this phenomenon has persisted for well over a century. it's simply nothing new -- like, the stock photographers who are most at risk from this already are already employed in an industry that itself decimated in-house illustration; think about how any dime-a-dozen reomance novel you can pick up at a store nowadays has a hastily photoshopped stock photo cover when fifty years ago it would have had a bespoke cover illustration that an artist got paid for.

of course, none of that historical overview is like, comforting to people who are currently worried about their lives getting worse, and i get that -- for those people, workplace organization and industrial action is the only realistic and productive avenue to mobilize those fears. the WGA and SAG-AFTRA strikes produced far more material concessions on gen-AI-based immseration for workers facing precarity than any amount of furious social media ludditism has

[vlruso]

Personalized Packaging Solutions: AIs Role in Customization

📢 Exciting News! 🎁 Personalized Packaging Solutions: AI's Role in Customization In today's world of personalization, AI is revolutionizing the way businesses enhance their product packaging process. 🌟 By leveraging AI capabilities, companies can create impactful and innovative personalized packaging solutions. AI's significance in the realm of product packaging cannot be overlooked. With personalization as a top priority, AI plays a pivotal role in improving this process. 🎯 Let's dive into how AI is being utilized in personalized packaging solutions and explore the future possibilities. 👉 Read more about this fascinating topic in our latest blog post here: https://ift.tt/k7HdK4b Have you tapped into the potential of AI for your packaging customization? It's time to explore the endless possibilities! 📦💡 #packaging #customization #AI #personalization #innovation List of Useful Links: AI Scrum Bot - ask about AI scrum and agile Our Telegram @itinai Twitter -  @itinaicom

[cnestus]

Hello !! I was wondering, is AI gonna have a role in your field?

I don't think there's a single knowledge-based profession out there that isn't under threat of being automated by some pig ignorant dipshit beancounting middle manager with a hardon for AI and entomology is certainly no exception. even before the big AI explosion of the last couple years people have been trying for a long time to automate pest arthropod identification, but at least so far they haven't been successful. Especially when it comes to things like bark beetles, which I specialize on, the differences between a harmless native species and an intensely destructive exotic one can be unbelievably subtle, not to mention the fact that new/cryptic species are always being discovered and that's not something an AI would ever be able to detect or understand.

That doesn't mean that our jobs aren't still under constant threat even by an algorithm that would do a piss-poor job of imitating us; the executive perverts that get all hot and bothered by the idea of replacing humans with fancified autocomplete functions have a vested interest in not understanding the nuances of the professions they're killing and as long as it's good enough or even just appears to be good enough, they'll push for it.

Also let's not forget one thing about "AI" which is that half the time it's actually just a marketing term used to cover up the usual outsourcing/offshoring to cheaper workforces that has been ongoing for the last 30 years. My lab was recently and repeatedly pestered by someone selling "AI moth traps" that purported to be able to identify any pest species of moth that flew into it. When we pressed him on it it turns out that part of the service it offered was that the moths would be photographed by a little digital camera in the device and the pics sent to a team of entomologists in Hungary to confirm. Aside from the fact that a lot of small moths need to be carefully examined under a microscope and often even have their genitalia dissected by an expert to be confirmed as a particular species, this is no different then any of the other supposed AI products that have been revealed over the last couple years as just being a shiny veneer over the same old digital sweatshops on the other side of the world.

More importantly though, even if the AI moth traps did work as advertised either through the ~*magic of machine learning*~ or desperate poorly paid eastern european entomologists either way it's yet another thin edge of the wedge designed to put me and my colleagues out of a job by convincing our bosses or our bosses' bosses that there's a cheaper and more efficient alternative and I view them and literally anything else marketed as AI as part of the same anti-human push to deskill and demoralize as much of the workforce as possible. I've never once used chatGPT or any other LLM, I've never used an AI image generator, and I will never, ever fucking use any purported AI entomology tool because aside from being shined up dogshit it is an existential threat to the discipline I've dedicated almost 20 years of my life to.

[mostlysignssomeportents]

AI can’t do your job

I'm on a 20+ city book tour for my new novel PICKS AND SHOVELS. Catch me in SAN DIEGO at MYSTERIOUS GALAXY on Mar 24, and in CHICAGO with PETER SAGAL on Apr 2. More tour dates here.

AI can't do your job, but an AI salesman (Elon Musk) can convince your boss (the USA) to fire you and replace you (a federal worker) with a chatbot that can't do your job:

https://www.pcmag.com/news/amid-job-cuts-doge-accelerates-rollout-of-ai-tool-to-automate-government

If you pay attention to the hype, you'd think that all the action on "AI" (an incoherent grab-bag of only marginally related technologies) was in generating text and images. Man, is that ever wrong. The AI hype machine could put every commercial illustrator alive on the breadline and the savings wouldn't pay the kombucha budget for the million-dollar-a-year techies who oversaw Dall-E's training run. The commercial market for automated email summaries is likewise infinitesimal.

The fact that CEOs overestimate the size of this market is easy to understand, since "CEO" is the most laptop job of all laptop jobs. Having a chatbot summarize the boss's email is the 2025 equivalent of the 2000s gag about the boss whose secretary printed out the boss's email and put it in his in-tray so he could go over it with a red pen and then dictate his reply.

The smart AI money is long on "decision support," whereby a statistical inference engine suggests to a human being what decision they should make. There's bots that are supposed to diagnose tumors, bots that are supposed to make neutral bail and parole decisions, bots that are supposed to evaluate student essays, resumes and loan applications.

The narrative around these bots is that they are there to help humans. In this story, the hospital buys a radiology bot that offers a second opinion to the human radiologist. If they disagree, the human radiologist takes another look. In this tale, AI is a way for hospitals to make fewer mistakes by spending more money. An AI assisted radiologist is less productive (because they re-run some x-rays to resolve disagreements with the bot) but more accurate.

In automation theory jargon, this radiologist is a "centaur" – a human head grafted onto the tireless, ever-vigilant body of a robot

Of course, no one who invests in an AI company expects this to happen. Instead, they want reverse-centaurs: a human who acts as an assistant to a robot. The real pitch to hospital is, "Fire all but one of your radiologists and then put that poor bastard to work reviewing the judgments our robot makes at machine scale."

No one seriously thinks that the reverse-centaur radiologist will be able to maintain perfect vigilance over long shifts of supervising automated process that rarely go wrong, but when they do, the error must be caught:

https://pluralistic.net/2024/04/01/human-in-the-loop/#monkey-in-the-middle

The role of this "human in the loop" isn't to prevent errors. That human's is there to be blamed for errors:

https://pluralistic.net/2024/10/30/a-neck-in-a-noose/#is-also-a-human-in-the-loop

The human is there to be a "moral crumple zone":

https://estsjournal.org/index.php/ests/article/view/260

The human is there to be an "accountability sink":

https://profilebooks.com/work/the-unaccountability-machine/

But they're not there to be radiologists.

This is bad enough when we're talking about radiology, but it's even worse in government contexts, where the bots are deciding who gets Medicare, who gets food stamps, who gets VA benefits, who gets a visa, who gets indicted, who gets bail, and who gets parole.

That's because statistical inference is intrinsically conservative: an AI predicts the future by looking at its data about the past, and when that prediction is also an automated decision, fed to a Chaplinesque reverse-centaur trying to keep pace with a torrent of machine judgments, the prediction becomes a directive, and thus a self-fulfilling prophecy:

https://pluralistic.net/2023/03/09/autocomplete-worshippers/#the-real-ai-was-the-corporations-that-we-fought-along-the-way

AIs want the future to be like the past, and AIs make the future like the past. If the training data is full of human bias, then the predictions will also be full of human bias, and then the outcomes will be full of human bias, and when those outcomes are copraphagically fed back into the training data, you get new, highly concentrated human/machine bias:

https://pluralistic.net/2024/03/14/inhuman-centipede/#enshittibottification

By firing skilled human workers and replacing them with spicy autocomplete, Musk is assuming his final form as both the kind of boss who can be conned into replacing you with a defective chatbot and as the fast-talking sales rep who cons your boss. Musk is transforming key government functions into high-speed error-generating machines whose human minders are only the payroll to take the fall for the coming tsunami of robot fuckups.

This is the equivalent to filling the American government's walls with asbestos, turning agencies into hazmat zones that we can't touch without causing thousands to sicken and die:

https://pluralistic.net/2021/08/19/failure-cascades/#dirty-data

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/2025/03/18/asbestos-in-the-walls/#government-by-spicy-autocomplete

Image: Krd (modified) https://commons.wikimedia.org/wiki/File:DASA_01.jpg

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

--

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

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

[sayruq]

A new investigation by +972 Magazine and Local Call reveals that the Israeli army has developed an artificial intelligence-based program known as “Lavender,” unveiled here for the first time. According to six Israeli intelligence officers, who have all served in the army during the current war on the Gaza Strip and had first-hand involvement with the use of AI to generate targets for assassination, Lavender has played a central role in the unprecedented bombing of Palestinians, especially during the early stages of the war. In fact, according to the sources, its influence on the military’s operations was such that they essentially treated the outputs of the AI machine “as if it were a human decision.”

During the early stages of the war, the army gave sweeping approval for officers to adopt Lavender’s kill lists, with no requirement to thoroughly check why the machine made those choices or to examine the raw intelligence data on which they were based. One source stated that human personnel often served only as a “rubber stamp” for the machine’s decisions, adding that, normally, they would personally devote only about “20 seconds” to each target before authorizing a bombing — just to make sure the Lavender-marked target is male. This was despite knowing that the system makes what are regarded as “errors” in approximately 10 percent of cases, and is known to occasionally mark individuals who have merely a loose connection to militant groups, or no connection at all. Moreover, the Israeli army systematically attacked the targeted individuals while they were in their homes — usually at night while their whole families were present — rather than during the course of military activity. According to the sources, this was because, from what they regarded as an intelligence standpoint, it was easier to locate the individuals in their private houses. Additional automated systems, including one called “Where’s Daddy?” also revealed here for the first time, were used specifically to track the targeted individuals and carry out bombings when they had entered their family’s residences.

The Lavender machine joins another AI system, “The Gospel,” about which information was revealed in a previous investigation by +972 and Local Call in November 2023, as well as in the Israeli military’s own publications. A fundamental difference between the two systems is in the definition of the target: whereas The Gospel marks buildings and structures that the army claims militants operate from, Lavender marks people — and puts them on a kill list. In addition, according to the sources, when it came to targeting alleged junior militants marked by Lavender, the army preferred to only use unguided missiles, commonly known as “dumb” bombs (in contrast to “smart” precision bombs), which can destroy entire buildings on top of their occupants and cause significant casualties. “You don’t want to waste expensive bombs on unimportant people — it’s very expensive for the country and there’s a shortage [of those bombs],” said C., one of the intelligence officers. Another source said that they had personally authorized the bombing of “hundreds” of private homes of alleged junior operatives marked by Lavender, with many of these attacks killing civilians and entire families as “collateral damage.”

Remember, the Israeli occupation government considers all men over the age of 16 to be Hamas operatives hence why they've claimed to have killed over 9,000 of them (which matches the number of Palestinian men killed according to the Ministry of Health). So, when the article speaks of 'low level' or 'high level militants' they're likely speaking of civilians.

If Israel knew who Hamas fighters are, Oct 7th wouldn't have caught them off guard and they wouldn't still be fighting the Palestinian resistance every single day.

[cupidsncheerios]

jayvik au where viktor is the name of an ai automated lab assistant in jayce’s workplace that operates various precision tools like the hexclaw, and viktor slowly gains sentience as the researchers shift his role from mechanical aid to full on lab butler getting coffee for them and shit

eventually viktor falls in love with jayce because jayce is the only person in this lab of complete assholes that says thank you after viktor helps them

[annarcho-nicolesmith]

Silicon Valley's Fish Killing Machine

There's a tech company called "Shinkei Systems" that created an "AI powered fish killing machine" (they're using an automated machine to do ike jime, a traditional Japanese slaughter technique where a fish is killed instantly via a knife to the brain). Here's a picture of their machine:

Isn't that metal box such a great way for a living creature to die? Shinkei systems claims this automated death machine is "more humane" than error prone humans, who of course, sometimes miss the mark when severing a fish's brain from its spinal cord.

If the idea of automated animal slaughter doesn't freak you out enough, take a look at their promotional material where they promise to "eliminate 85% of the workforce" wherever their machine is used.

And just to wrap this story up in a bow, the founder is a guy named Saif Khawaja who retweets a lot about "DNA based IQ testing" and other race-science nonsense:

So yeah....a tech company run by a race obsessed skull-measurer decided the most pressing issue facing the world was not enough cheap sushi-grade salmon. The solution, of course, isn't to allow the ocean's depleted fisheries to regain their natural levels by reducing commercial fishing, it's to make a robot that can kill fish in a fancy Japanese way so people who eat industrialy farmed animals can feel less bad about it. And why not put a bunch of fishermen out of work while you're at it? The solution to our ever alienated world is clearly removing any human contact in the food supply and ceding that role to a machine. Clearly, the faster we can kill animals the better; perhaps we can kill them quickly before any concerns about the rapid destruction of the earth's aquatic ecosystems arise out of our collective haunted consciousness.