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aiphilosophy · 1 year

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Ai taking over the world

Artificial intelligence (AI) has been a hot topic in recent years, with many experts predicting that it will have a significant impact on the future of humanity. Some people have even gone as far as to suggest that AI could eventually "take over the world."

While it's true that AI has the potential to be incredibly powerful, the idea that it will take over the world is more science fiction than science fact. There are several reasons why this is unlikely to happen.

First, it's important to remember that AI is simply a tool. It doesn't have its own goals or motivations. It can only do what it's programmed to do. This means that any potential negative effects of AI would be the result of human decisions, not the technology itself.

Second, there are many organizations and individuals working to ensure that AI is developed and used ethically. Researchers, policymakers, and industry leaders are all working to establish guidelines and best practices for the development and use of AI.

Third, it's important to remember that AI is not a monolithic technology. There are many different types of AI, and each has its own strengths and weaknesses. For example, machine learning and deep learning are used to analyze data and make predictions, while natural language processing is used to understand and respond to human language.

Ultimately, while it's true that AI has the potential to change the world in many ways, it's unlikely that it will take over the world. As long as we continue to develop and use AI responsibly, we can reap the benefits of this powerful technology while minimizing any potential negative effects.

In summary, it's a myth that AI will take over the world. AI is a tool, and it's the humans who operate and regulate its use. There are several organizations and individuals working to ensure that AI is developed and used ethically. It's important to remember that AI is not a monolithic technology, and each has its own strengths and weaknesses. Therefore, we must use AI responsibly to reap the benefits of this powerful technology while minimizing any potential negative effects

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jcmarchi · 2 months

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AI in Marketing: MWC Conference Insights

New Post has been published on https://thedigitalinsider.com/ai-in-marketing-mwc-conference-insights/

AI in Marketing: MWC Conference Insights

In the dynamic intersection of technology and creativity, AI in Marketing stands as a transformative force, reshaping the essence of how brands engage with their audiences. The “Unleashing creativity through the human-robot duality in marketing” panel at the 4YFN event, part of the recent Mobile World Congress (MWC) Conference, spotlighted this evolution. Featuring insights from leaders like Mariam Asmar, Aitor Abonjo, Melissa Kruse, and Tzvika Besor, the panel delved into the intricate dance between AI and human innovation in marketing, revealing a future where these entities don’t just coexist but synergize to unlock new realms of possibility.

The central theses of the MWC’s 4YFN panel was that AI in Marketing is more than a tool; it’s a creative partner. This article explores AI’s impact on marketing, highlighting how it enhances creativity, customer engagement, operational efficiency, and message precision.

The Evolution of Marketing Through AI

The Strategic Role of AI

The integration of AI in marketing strategies has been transformative, primarily through its ability to analyze and leverage big data with unprecedented accuracy. Aitor Abonjo, highlighted this shift, emphasizing how AI enables the identification of the most accurate user base for testing, thereby enhancing the relevance and impact of marketing campaigns. This strategic application of AI ensures that marketing efforts are not only more efficient but also more effective, targeting consumers with precision previously unattainable.

Enhancing Efficiency and Creativity

AI’s role in streamlining operations and fostering creativity has been significant. Melissa Kruse shared insights on using AI tools for brainstorming and drafting, noting how they speed up the creative process while ensuring a high level of personalization. This efficiency not only reduces operational costs but also allows marketing teams to allocate more time to innovate and experiment with new ideas. The concept of using AI, like ChatGPT+, as Kruse suggests, transforms it from a tool into a team member, capable of contributing creatively to marketing strategies.

Personalization at Scale

Tzvika Besor discussed the transformative power of AI in achieving personalization at an unprecedented scale. By tailoring specific messaging for individual consumers, AI tools enable a level of personalization that was once beyond reach. Besor’s insights underscore the importance of AI in crafting marketing messages that resonate personally with consumers, enhancing engagement and fostering deeper connections between brands and their audiences.

Enhancing Creativity and Personalization with AI

Tailoring Messages with Precision

AI’s ability to sift through data and unearth consumer insights has revolutionized the way marketing messages are crafted. Tzvika Besor highlighted the potential for AI tools to allow for hyper-personalized messaging, emphasizing that creative marketing is no longer a one-size-fits-all endeavor. By understanding individual preferences and behaviors, AI enables marketers to create content that speaks directly to the consumer, making each interaction more meaningful and impactful.

Streamlining the Creative Process

Melissa Kruse shared insights into how AI is being used as a powerful assistant in the brainstorming and drafting phases of content creation. AI’s capacity to generate ideas and refine concepts has not only sped up these processes but also introduced a level of creativity that was previously unattainable. This synergy between human creativity and AI’s computational power is pushing the boundaries of what’s possible in marketing content, opening doors to innovative approaches and themes.

Reducing Costs, Maximizing Impact

The integration of AI in creative strategies has also had a significant effect on the economics of marketing campaigns. As Tzvika Besor pointed out, the costliness of creative endeavors, traditionally a major concern for marketing departments, is being mitigated by AI’s efficiency and versatility. The ability of AI to tailor messaging for individual users without requiring extensive human labor allows for more ambitious campaigns with lower resource investment.

AI’s Role in Strategic Decision-Making

Optimizing Marketing Strategies with Data

The strategic incorporation of AI into marketing decision-making processes marks a significant leap towards data-driven strategies. Aitor Abonjo shed light on how AI technologies like predictive analytics and machine learning are pivotal in understanding market trends and consumer behaviors. These tools not only offer a granular view of the current market landscape but also forecast future shifts, enabling marketers to adapt their strategies proactively rather than reactively. The ability to anticipate consumer needs and market dynamics positions brands to capitalize on opportunities with agility and precision.

Enhancing Consumer Engagement Through Insights

The depth and breadth of insights provided by AI extend beyond market analysis, delving into the nuances of consumer engagement. Melissa Kruse emphasized the role of AI in dissecting consumer feedback and online interactions to refine marketing messages and tactics. This ongoing analysis allows brands to maintain a pulse on consumer sentiment, fostering a level of engagement that resonates on a personal level. By leveraging AI, marketers can transform raw data into actionable insights, crafting campaigns that speak directly to the evolving interests and preferences of their audience.

Streamlining Operations and Reducing Costs

Beyond the external focus on markets and consumers, AI’s strategic value also lies in its ability to streamline internal operations. Aitor Abonjo highlighted the operational efficiencies gained from implementing AI tools, such as reduced time to market and lower operational costs. These efficiencies not only improve the bottom line but also free up resources that can be redirected towards innovation and creative endeavors, further amplifying a brand’s competitive edge.

Operational Efficiency and Problem Solving

The integration of AI into marketing operations has revolutionized how businesses approach problem-solving and efficiency. By automating routine tasks and optimizing workflows, AI technologies are enabling marketing teams to focus on strategic and creative work, significantly enhancing productivity and reducing operational costs.

Automating Routine Tasks for Efficiency

One of the most immediate impacts of AI on marketing operations is the automation of time-consuming tasks. Aitor Abonjo discussed how AI tools have been instrumental in streamlining content creation processes and administrative tasks. This automation extends beyond mere content production to include data analysis, customer service inquiries, and even the optimization of digital ad placements. By handling these routine operations, AI allows teams to allocate their time and resources more effectively, focusing on initiatives that require human creativity and strategic thinking.

Enhancing Problem-Solving Capabilities

Beyond routine automation, AI’s role in problem-solving within marketing operations is profound. AI systems are capable of identifying issues in real-time, from detecting shifts in consumer behavior to pinpointing inefficiencies in marketing campaigns. This rapid problem identification enables swift adjustments, ensuring that marketing strategies remain agile and responsive to the market’s demands. Furthermore, AI-driven tools are increasingly used for predictive analysis, forecasting potential challenges and allowing teams to devise proactive solutions, thereby minimizing risks and maximizing opportunities.

Streamlining Communication and Collaboration

AI technologies also play a critical role in enhancing communication and collaboration within marketing teams and between different departments. Tools powered by AI facilitate the seamless sharing of insights and data, breaking down silos and fostering a more integrated approach to marketing strategy and execution. As Tzvika Besor emphasized, the ability of AI to connect various aspects of the business is pivotal, ensuring that all team members are aligned and informed, thus enhancing overall operational efficiency.

Privacy, Ethics, and the Future of AI in Marketing

As AI becomes increasingly embedded in marketing strategies, its implications on privacy and ethical considerations come to the forefront. The transformative potential of AI in marketing is vast, but it must be navigated carefully to uphold consumer trust and adhere to evolving regulatory landscapes.

Navigating Privacy Concerns

The capacity of AI to collect, analyze, and act on vast amounts of data raises significant privacy concerns. Tzvika Besor highlighted the delicate balance between leveraging AI for personalized marketing and respecting individual privacy rights. Advanced AI tools can tailor marketing efforts to individual preferences with unprecedented precision, yet this capability necessitates a cautious approach to data handling and consent mechanisms. Marketers must ensure that AI-driven initiatives comply with privacy regulations like GDPR and CCPA, prioritizing transparency and consumer control over personal data.

Ethical Use of AI in Marketing

Ethical considerations extend beyond privacy to include the integrity of marketing practices influenced by AI. The panel discussion emphasized the importance of using AI to enhance consumer experiences without resorting to manipulative tactics. AI’s ability to influence purchasing decisions through personalized content and recommendations carries the responsibility to avoid exploiting vulnerabilities or biases in consumer behavior. Ethical AI use in marketing means committing to fairness, accuracy, and accountability, ensuring that AI-driven strategies benefit both the brand and its audience.

The Interplay of AI and Human Creativity

The fusion of AI and human creativity in marketing represents a paradigm shift, offering a new realm of possibilities for innovation and engagement. This interplay is not a matter of replacing human insight but augmenting it, creating a symbiotic relationship that elevates the creative process.

Amplifying Creative Potential

AI’s role in marketing extends beyond analytical and operational tasks, entering the creative domain where it acts as a catalyst for human creativity. Tools like ChatGPT have revolutionized content creation, providing initial drafts and ideas that marketing professionals can refine and enhance. This partnership allows for a higher volume of creative output without compromising quality, as AI handles the heavy lifting of data analysis and pattern recognition, freeing humans to focus on the artistry and emotional resonance of marketing content.

Personalization and Storytelling

These Insights highlight how AI enables a level of personalization in marketing that was previously unimaginable. By understanding individual consumer preferences and behaviors, AI helps craft narratives that speak directly to the audience, making each marketing message feel bespoke. This personalized storytelling not only improves engagement rates but also strengthens the emotional connection between brands and their consumers, a feat that requires the nuanced understanding of human marketers guided by AI’s data-driven insights.

Ethical and Authentic Engagement

As the capabilities of AI in marketing evolve, so does the importance of maintaining an ethical approach to its use. The interplay between AI and human creativity must be navigated with a commitment to authenticity and ethical principles. AI can identify trends and optimize messaging, but the human element is essential to ensure that these strategies are implemented in a way that respects consumer privacy and promotes genuine engagement. The blend of AI’s efficiency and human empathy creates a marketing approach that is not only effective but also respectful and authentic.

The Future of Collaborative Creativity

Looking forward, the collaboration between AI and human creativity in marketing is set to deepen, with AI tools becoming more integrated into the creative process. As these technologies continue to evolve, the potential for innovative marketing strategies that seamlessly blend data-driven insights with human intuition and creativity is immense. However, the success of this collaboration hinges on the ability of marketers to remain at the forefront of AI developments, steering these advancements in a direction that enhances rather than diminishes the human touch.

The partnership between AI and human creativity in marketing is a testament to the potential of technology to enhance human capabilities. As we navigate this evolving landscape, the key to unlocking the full potential of AI in marketing lies in leveraging its strengths to amplify human creativity, ensuring that marketing remains a profoundly human-centric endea3vor.

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nitor-infotech · 5 months

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In 2023, the BFSI sector, with an estimated worth of $179 billion, undergoes a sweeping transformation. This evolution, driven by innovations such as GenAI, IoT, and other digital solutions, presents a landscape teeming with both opportunities and challenges. By exploring this blog, you'll gain invaluable insights into the core issues and practical solutions that will enable your business to navigate the dynamic financial industry seamlessly. Knowing about these advancements will empower you to make informed decisions in the rapidly changing banking terrain, ensuring that you remain at the forefront.

#compliance management systems #digital transformation #project management #it digital transformation #a digital transformation #data and analysis #software companies #data in analytics #big data #business analytics #business intelligence #digital products #products management

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datatofu · 6 months

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Data-Driven Data Protection and Privacy

There is a distinct disparity in data handling and data privacy. Specifically, companies tend only to apply cyber security standards and metrics to themselves rather than their customers. Instead, provider performance determines most company sentiment toward their consumers. Company cyber security metrics encompass geographic orientation, control visibility for redundant cloud applications,…

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#ai #big data #big data analytics #data infrastructure #socio-technical system #technology

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atozofsoftwareengineering · 8 months

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Exploring Amazon EC2: Unveiling the Why, Where, and How of Cloud Computing's Backbone

Hey friends! 🌟 Dive into a comprehensive guide on mastering Amazon EC2 for cloud computing excellence. From cost efficiency to web hosting, #EC2Mastery unlocks the secrets of scalability, security, and innovation. 💡🚀 #CloudComputing #AWS

In today’s dynamic world of cloud computing, where businesses and developers demand ever-increasing flexibility, scalability, and efficiency, Amazon Elastic Compute Cloud (EC2) stands as an unshakable pillar. This article ventures deep into the realm of Amazon EC2, peeling back layers to reveal the motivations driving its widespread adoption, the scenarios where it shines with brilliance, and an…

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educationisimp0 · 9 months

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Data Analytics Technology - Data analytics technologies are constantly evolving and will become more complex over the years. Let's explore top data analytics technologies businesses should be aware of in 2023

#Data analytics technology #analytics technology #data management #big data analytics #predictive analytics #big data analytics technology #data quality #data science #business decisions #management systems

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qwikskills · 1 year

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Unleashing the Power of Machine Learning in the 21st Century

Machine learning is one of the most talked about and rapidly growing fields in the tech industry. It is a branch of artificial intelligence that allows computers to learn and make predictions or decisions without explicit programming. The rise of big data and the increasing availability of computing power have made it possible for machine learning algorithms to handle vast amounts of data and provide valuable insights and predictions.

In recent years, machine learning has been applied in various industries, ranging from healthcare to finance, retail, and marketing. In healthcare, machine learning algorithms are used to analyze patient data and help doctors make more accurate diagnoses. In finance, machine learning is used to detect fraud, analyze financial markets, and make investment decisions. In retail, machine learning is used to personalize shopping experiences, recommend products, and optimize pricing.

One of the key benefits of machine learning is that it allows for automated decision-making, which can save time and resources. Machine learning algorithms can analyze large amounts of data and provide insights in real-time, enabling organizations to make data-driven decisions more efficiently. Additionally, machine learning algorithms are able to improve over time, becoming more accurate as they are exposed to more data.

Despite its many advantages, machine learning is not without its challenges. One of the main challenges is the lack of transparency in decision-making. It can be difficult to understand how machine learning algorithms arrived at a particular decision, making it difficult to explain the decision to stakeholders. Additionally, machine learning algorithms can be biased if the data used to train them is biased, leading to unfair or inaccurate decisions.

In conclusion, machine learning is a powerful tool that has the potential to transform the way we live and work. As the technology continues to evolve and improve, we can expect to see more and more applications of machine learning in various industries. However, it is important to approach machine learning with caution and ensure that the algorithms are developed and used in a transparent and ethical manner.

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hdatabhavesh · 2 years

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Fundaments of an Analytics and AI Strategy - HData Systems

Without a clear strategy and vision, many firms experience technological stasis since the platforms they initially selected aren’t scalable or equipped to accommodate cutting-edge AI as it advances. A bad strategy leads to isolated projects that don’t collaborate to develop a cohesive AI program. Evaluative and implementable solutions for artificial intelligence are essential. They produce outcomes and are based on practitioners’ actual field experience using AI.

Your business will generate more and more data as it expands. A successful AI strategy will ensure that the information growth translates into business value, just as having an effective data strategy will ensure that it can be managed appropriately. Using your data,

Sort customers and goods into categories based on shared wants and habits.

Forecast client spending and churn risk.

Calculate a product’s or customer’s lifetime value.

Increase uptime by doing predictive maintenance and streamlining manufacturing supply chains.

The fact that many businesses lack big data analytics and AI strategy is a major factor in the lack of strategic value. Although some might doubt the value of a strategy for a certain technology, one is necessary when that technology can fundamentally alter a company’s operations.

Executives would be more inclined to believe that the technologies were essential to their capacity to compete if analytics and AI initiatives were widespread and institutionalized in businesses. Their societies would place a strong emphasis on making analytical decisions. They would perceive analytics, AI, and data as crucial components of company innovation and significant business assets.

Who Generates The Strategy?

A corporation may or may not have qualified employees to create analytics or AI strategy. This kind of strategy formulation necessitates fusing in-depth topic expertise with broad knowledge of analytics and AI capabilities. Aspirants should have the following characteristics:

They should be familiar with the main categories of analytics and AI technology, how businesses use them, and potential integrations with other information technologies.

They ought to have good non-technical communication skills with supervisors.

They should possess in-depth knowledge of the specific business fields in which analytics and AI will be used, as well as the key concerns facing the company generally and its present strategic orientation.

Given that they will be rethinking how consumers, partners, and workers engage with the business, they ought to be conversant with design thinking.

The same goes for facilitation and process skills when developing various.

Of course, not every member of a team developing a strategy will possess each of these abilities. It’s acceptable if they are dispersed among the squad. Due to the diversity of the required skills, the development team should typically include experts in analytics and artificial intelligence (AI), as well as business leaders who are knowledgeable about the subject. If members of the analytics strategy team lack some of the necessary knowledge, they can engage a data science company.

Also Read, Importance And Benefits Of Artificial Intelligence

The Outcomes of a Data Analytics Strategy

Big data analytics is used to examine massive amounts of data in order to uncover previously unrecognized patterns, correlations, and other insights. With today’s technology, you can quickly analyze your big data in business and obtain insights from it, whereas this process would take longer and be less effective with more conventional business intelligence tools.

Analytics and AI strategy’s objective is to identify, address, and reach organizational consensus on important questions and directions for these resources, as is the case with most strategies. Without a plan, judgments about analytics and AI may be haphazard or unproductive.

There are numerous crucial decisions to be taken. With a subpar or nonexistent plan, businesses risk wasting time and money on these technologies. Although it is a useful technique, an “agile” approach to analytics and AI, in which businesses explore, fail, learn, and repeat experiments, is not a strategy.

An analytics and AI strategy primarily serve two goals, to be more precise. One is to support the use of these resources by the entire organization. A plan would cover issues like what applications or use cases the organization should concentrate on, the types of talent it needs, the types of data it needs, and other similar issues. Every function and unit within the organisation should, at some point, be responsible for analytics and AI, and they should all use the plan to guide their AI projects.

The Structure of Strategy

In the modern day, artificial intelligence, or AI, and data science have emerged as the two most essential and sought-after technologies. Companies adopt several methods to determine their strategies, An pure ad hoc strategy is unlikely to provide a rigorous and evidence-based conclusion, and a unilateral approach by the CEO — or even the leader of the analytics and AI function — is unlikely to engage the enterprise. Interviews with internal and external experts, workshops, and strategy review sessions should all be a part of the process. The intention is to discuss the potential for transformative change and previously unsolved business issues.

Instead of creating a strategy document, the process’s objective should be to inspire thoughtful and informed action. An effective strategy will frequently result in several pilots, proofs of concept, or production deployments of analytics and AI across the business. It ought to include a strategy for retraining managers and staff to lead and run cognitively driven companies. issues that have never been resolved.

Before beginning a strategy attempt, it is frequently a good idea to assess current capabilities because an analytics and AI plan is typically meant to increase capabilities and outcomes. The strategy document might outline the means through which the organisation plans to enhance its capabilities by describing the current status of analytics and AI.

Also Read

How to Use AI in Mobile Applications in 2022

What Are The Pros And Cons of DevOps

Ultimate IoT Implementation Guide For Businesses

Artificial Intelligence In The Metaverse

Originally published at https://www.hdatasystems.com.

#ai #artificial intelligence #analytics #hdata systems #data science #big data #business

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xevensolution · 2 years

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AI Bot: The Application of Data Science in the Tech Industry

The advancement of data science and sophisticated types of analytics has resulted in a wide range of applications that provide superior insights and commercial value to businesses for AI Bot. Data science methods, approaches, tools, and AI Bot Software, in particular, provide companies with the tools they need to extract useful information from ever-increasing volumes of highly varied data.

#technology healthcare #big data analytics #AI Bot Software #hrm management system #AI Bot

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mostlysignssomeportents · 7 months

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The surveillance advertising to financial fraud pipeline

Monday (October 2), I'll be in Boise to host an event with VE Schwab. On October 7–8, I'm in Milan to keynote Wired Nextfest.

Being watched sucks. Of all the parenting mistakes I've made, none haunt me more than the times my daughter caught me watching her while she was learning to do something, discovered she was being observed in a vulnerable moment, and abandoned her attempt:

https://www.theguardian.com/technology/blog/2014/may/09/cybersecurity-begins-with-integrity-not-surveillance

It's hard to be your authentic self while you're under surveillance. For that reason alone, the rise and rise of the surveillance industry – an unholy public-private partnership between cops, spooks, and ad-tech scum – is a plague on humanity and a scourge on the Earth:

https://pluralistic.net/2023/08/16/the-second-best-time-is-now/#the-point-of-a-system-is-what-it-does

But beyond the psychic damage surveillance metes out, there are immediate, concrete ways in which surveillance brings us to harm. Ad-tech follows us into abortion clinics and then sells the info to the cops back home in the forced birth states run by Handmaid's Tale LARPers:

https://pluralistic.net/2022/06/29/no-i-in-uter-us/#egged-on

And even if you have the good fortune to live in a state whose motto isn't "There's no 'I" in uter-US," ad-tech also lets anti-abortion propagandists trick you into visiting fake "clinics" who defraud you into giving birth by running out the clock on terminating your pregnancy:

https://pluralistic.net/2023/06/15/paid-medical-disinformation/#crisis-pregnancy-centers

The commercial surveillance industry fuels SWATting, where sociopaths who don't like your internet opinions or are steamed because you beat them at Call of Duty trick the cops into thinking that there's an "active shooter" at your house, provoking the kind of American policing autoimmune reaction that can get you killed:

https://www.cnn.com/2019/09/14/us/swatting-sentence-casey-viner/index.html

There's just a lot of ways that compiling deep, nonconsensual, population-scale surveillance dossiers can bring safety and financial harm to the unwilling subjects of our experiment in digital spying. The wave of "business email compromises" (the infosec term for impersonating your boss to you and tricking you into cleaning out the company bank accounts)? They start with spear phishing, a phishing attack that uses personal information – bought from commercial sources or ganked from leaks – to craft a virtual Big Store con:

https://www.fbi.gov/how-we-can-help-you/safety-resources/scams-and-safety/common-scams-and-crimes/business-email-compromise

It's not just spear-phishers. There are plenty of financial predators who run petty grifts – stock swindles, identity theft, and other petty cons. These scams depend on commercial surveillance, both to target victims (e.g. buying Facebook ads targeting people struggling with medical debt and worried about losing their homes) and to run the con itself (by getting the information needed to pull of a successful identity theft).

In "Consumer Surveillance and Financial Fraud," a new National Bureau of Academic Research paper, a trio of business-school profs – Bo Bian (UBC), Michaela Pagel (WUSTL) and Huan Tang (Wharton) quantify the commercial surveillance industry's relationship to finance crimes:

https://www.nber.org/papers/w31692

The authors take advantage of a time-series of ZIP-code-accurate fraud complaint data from the Consumer Finance Protection Board, supplemented by complaints from the FTC, along with Apple's rollout of App Tracking Transparency, a change to app-based tracking on Apple mobile devices that turned of third-party commercial surveillance unless users explicitly opted into being spied on. More than 96% of Apple users blocked spying:

https://arstechnica.com/gadgets/2021/05/96-of-us-users-opt-out-of-app-tracking-in-ios-14-5-analytics-find/

In other words, they were able to see, neighborhood by neighborhood, what happened to financial fraud when users were able to block commercial surveillance.

What happened is, fraud plunged. Deprived of the raw material for committing fraud, criminals were substantially hampered in their ability to steal from internet users.

While this is something that security professionals have understood for years, this study puts some empirical spine into the large corpus of qualitative accounts of the surveillance-to-fraud pipeline.

As the authors note in their conclusion, this analysis is timely. Google has just rolled out a new surveillance system, the deceptively named "Privacy Sandbox," that every Chrome user is being opted in to unless they find and untick three separate preference tickboxes. You should find and untick these boxes:

https://www.eff.org/deeplinks/2023/09/how-turn-googles-privacy-sandbox-ad-tracking-and-why-you-should

Google has spun, lied and bullied Privacy Sandbox into existence; whenever this program draws enough fire, they rename it (it used to be called FLoC). But as the Apple example showed, no one wants to be spied on – that's why Google makes you find and untick three boxes to opt out of this new form of surveillance.

There is no consensual basis for mass commercial surveillance. The story that "people don't mind ads so long as they're relevant" is a lie. But even if it was true, it wouldn't be enough, because beyond the harms to being our authentic selves that come from the knowledge that we're being observed, surveillance data is a crucial ingredient for all kinds of crime, harassment, and deception.

We can't rely on companies to spy on us responsibly. Apple may have blocked third-party app spying, but they effect nonconsensual, continuous surveillance of every Apple mobile device user, and lie about it:

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

That's why we should ban commercial surveillance. We should outlaw surveillance advertising. Period:

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

Contrary to the claims of surveillance profiteers, this wouldn't reduce the income to ad-supported news and other media – it would increase their revenues, by letting them place ads without relying on the surveillance troves assembled by the Google/Meta ad-tech duopoly, who take the majority of ad-revenue:

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

We're 30 years into the commercial surveillance pandemic and Congress still hasn't passed a federal privacy law with a private right of action. But other agencies aren't waiting for Congress. The FTC and DoJ Antitrust Divsision have proposed new merger guidelines that allow regulators to consider privacy harms when companies merge:

https://www.regulations.gov/comment/FTC-2023-0043-1569

Think here of how Google devoured Fitbit and claimed massive troves of extremely personal data, much of which was collected because employers required workers to wear biometric trackers to get the best deal on health care:

https://www.eff.org/deeplinks/2020/04/google-fitbit-merger-would-cement-googles-data-empire

Companies can't be trusted to collect, retain or use our personal data wisely. The right "balance" here is to simply ban that collection, without an explicit opt-in. The way this should work is that companies can't collect private data unless users hunt down and untick three "don't spy on me" boxes. After all, that's the standard that Google has set.

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/2023/09/29/ban-surveillance-ads/#sucker-funnel

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

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

#pluralistic #commercial surveillance #surveillance #surveillance advertising #ad-tech #behavioral advertising #ads #privacy #fraud #targeting #ad targeting #scams #scholarship #nber #merger guidelines #ftc #doj

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phonesuitedirect · 1 month

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In this article, we explore the transformative potential of big data for predictive analytics and decision-making in the hospitality industry. Read More...

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qqueenofhades · 5 months

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I’m in undergrad but I keep hearing and seeing people talking about using chatgpt for their schoolwork and it makes me want to rip my hair out lol. Like even the “radical” anti-chatgpt ones are like “Oh yea it’s only good for outlines I’d never use it for my actual essay.” You’re using it for OUTLINES????? That’s the easy part!! I can’t wait to get to grad school and hopefully be surrounded by people who actually want to be there 😭😭😭

Not to sound COMPLETELY like a grumpy old codger (although lbr, I am), but I think this whole AI craze is the obvious result of an education system that prizes "teaching for the test" as the most important thing, wherein there are Obvious Correct Answers that if you select them, pass the standardized test and etc etc mean you are now Educated. So if there's a machine that can theoretically pick the correct answers for you by recombining existing data without the hard part of going through and individually assessing and compiling it yourself, Win!

... but of course, that's not the way it works at all, because AI is shown to create misleading, nonsensical, or flat-out dangerously incorrect information in every field it's applied to, and the errors are spotted as soon as an actual human subject expert takes the time to read it closely. Not to go completely KIDS THESE DAYS ARE JUST LAZY AND DONT WANT TO WORK, since finding a clever way to cheat on your schoolwork is one of those human instincts likewise old as time and has evolved according to tools, technology, and educational philosophy just like everything else, but I think there's an especial fear of Being Wrong that drives the recourse to AI (and this is likewise a result of an educational system that only prioritizes passing standardized tests as the sole measure of competence). It's hard to sort through competing sources and form a judgment and write it up in a comprehensive way, and if you do it wrong, you might get a Bad Grade! (The irony being, of course, that AI will *not* get you a good grade and will be marked even lower if your teachers catch it, which they will, whether by recognizing that it's nonsense or running it through a software platform like Turnitin, which is adding AI detection tools to its usual plagiarism checkers.)

We obviously see this mindset on social media, where Being Wrong can get you dogpiled and/or excluded from your peer groups, so it's even more important in the minds of anxious undergrads that they aren't Wrong. But yeah, AI produces nonsense, it is an open waste of your tuition dollars that are supposed to help you develop these independent college-level analytical and critical thinking skills that are very different from just checking exam boxes, and relying on it is not going to help anyone build those skills in the long term (and is frankly a big reason that we're in this mess with an entire generation being raised with zero critical thinking skills at the exact moment it's more crucial than ever that they have them). I am mildly hopeful that the AI craze will go bust just like crypto as soon as the main platforms either run out of startup funding or get sued into oblivion for plagiarism, but frankly, not soon enough, there will be some replacement for it, and that doesn't mean we will stop having to deal with fake news and fake information generated by a machine and/or people who can't be arsed to actually learn the skills and abilities they are paying good money to acquire. Which doesn't make sense to me, but hey.

So: Yes. This. I feel you and you have my deepest sympathies. Now if you'll excuse me, I have to sit on the porch in my quilt-draped rocking chair and shout at kids to get off my lawn.

#anonymous #ask #school stuff

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jcmarchi · 3 months

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Unite.AI Launches Premium .AI Domain Name Marketplace

New Post has been published on https://thedigitalinsider.com/unite-ai-launches-premium-ai-domain-name-marketplace/

Unite.AI Launches Premium .AI Domain Name Marketplace

In a strategic move to address a significant gap in the domain marketplace, Unite.AI has launched a premium .AI domain name marketplace. This pioneering initiative aims to create a dedicated platform for startups and enterprises to access and select from a curated list of premium .AI domains. The decision was driven by the realization that there is no existing marketplace catering specifically to the growing demand for upscale .AI domain names, which have become increasingly valuable due to the rising prominence of Artificial Intelligence (AI) in various industries.

.AI domains have emerged as a symbol of innovation and cutting-edge technology, making them highly sought after by companies in the AI space. Recognizing this trend, Unite.AI identified an opportunity to facilitate easier access to these domains, thereby empowering businesses to secure a digital identity that aligns with their AI-focused branding and operations.

The marketplace’s launch is marked by the listing of its first domain name, Images.AI. This domain was previously used for an image generation service, which as of January 17, 2024 ceased operations. The availability of Images.AI as the inaugural listing not only underscores the high caliber of domains on offer but also illustrates the marketplace’s potential to repurpose valuable digital assets for new ventures and innovations.

By offering a specialized platform for .AI domains, Unite.AI is not only simplifying the process of obtaining these niche domain names but is also playing a crucial role in shaping the digital landscape of AI businesses. This marketplace is poised to become a pivotal resource for companies seeking to establish a strong online presence in the AI industry, underlining Unite.AI’s commitment to fostering growth and innovation in this dynamic sector.

First Batch of Premium .AI Domain Names

The first batch of .AI domain names offered through Unite.AI’s premium marketplace includes a diverse and promising range of options, each with its unique potential for business applications in the AI sector. Let’s explore these domains and their potential uses:

Think.AI: This domain is ideal for AI consulting or solutions firms. It symbolizes businesses that are focused on developing and implementing innovative AI strategies. Think.AI could become a leading name in the industry, representing expertise in cutting-edge AI solutions and strategic AI planning.

Driven.AI: Suited for companies specializing in AI analytics and automation, Driven.AI is a perfect fit for businesses at the forefront of AI-powered data analysis and autonomous systems. This includes areas like self-driving technology, making it a highly relevant and future-facing domain.

OpenRobot.AI: Targeting open-source robotics ventures, OpenRobot.AI is a fitting domain for companies ranging from collaborative robotics to educational robotics platforms. This domain fosters a community-oriented approach, appealing to both robotics enthusiasts and professionals.

HumanX.AI: This domain is tailored for companies dedicated to human-centric AI applications. Businesses under HumanX.AI could focus on enhancing human capabilities through AI in sectors like healthcare and personalized learning, emphasizing the human element in AI.

Technology.AI: A broad yet impactful domain, Technology.AI is ideal for a comprehensive AI technology company. This domain can encompass a wide array of AI solutions, from software development to technological innovations across various industries, making it a versatile and potent choice.

Genes.AI: This domain is ideal for AI ventures at the intersection of genomics and bioinformatics. Companies using Genes.AI could lead the way in applying AI to genetics research, personalized medicine, and biotech innovations, marking a significant step forward in AI applications in life sciences.

Nanobots.AI: Suggestive of a focus on AI in nanotechnology, Nanobots.AI is suitable for businesses developing AI-powered microscopic robots for applications in medicine, manufacturing, or environmental fields. This domain indicates a futuristic vision of AI’s role in nanoscale interventions.

RobotX.AI: Ideal for cutting-edge robotics companies, RobotX.AI represents a domain at the forefront of robotic innovation. Businesses under this domain could specialize in advanced robotic systems, AI-driven automation, and next-generation robotics solutions, catering to industries ranging from manufacturing to healthcare. RobotX.AI suggests a brand deeply ingrained in the development of sophisticated, AI-enhanced robots that are transforming the way we work and live.

BigData.AI: This domain is perfectly suited for companies specializing in big data analytics and AI-driven data solutions. BigData.AI could become a leading name in the field of data science, offering services like predictive analytics, data mining, and AI-powered insights. This domain would appeal to businesses focused on harnessing the power of big data to drive decision-making and innovation across various sectors, from finance to healthcare, emphasizing the integral role of AI in extracting value from large data sets.

Images.AI: Perfect for businesses in AI-driven image processing and generation, Images.AI represents an ideal domain for companies at the cutting edge of visual AI technology. This domain could become a hub for AI advancements in image recognition, digital art, and visual analytics, offering a prime digital identity for businesses specializing in leveraging AI to revolutionize how we process, interpret, and create images. Images.AI is an excellent choice for companies seeking to establish themselves as leaders in the rapidly evolving field of AI-based imaging solutions

Each of these domains not only offers a unique digital identity but also opens avenues for innovation and growth in their respective AI-related fields, making them valuable assets for any forward-thinking business in the AI arena.

Premium AI Domain Names at Unite.AI: Exclusively Serving the AI Sector

The Unite.AI domain name marketplace stands out as the first premium marketplace dedicated exclusively to serving the AI sector. This specialization is significant in an industry that is rapidly evolving and highly specialized. By focusing solely on premium AI domain names, Unite.AI ensures that businesses in this sector have access to the most relevant, impactful, and brandable online identities.

For Sellers: Pitching Your Domain Name

Unite.AI’s premium AI domain name marketplace is not just a destination for buyers; it also offers an invaluable platform for sellers looking to pitch their high-quality AI domain names. Understanding the importance of connecting sellers with the right audience, Unite.AI has streamlined the process to ensure a smooth and effective selling experience.

The platform offer a Risk-Free Listing opportunity. One of the key features of this marketplace is the risk-free nature of listing a domain name. Sellers can list their domains without any upfront fees, making it accessible and appealing for anyone with a premium AI domain.

Instead of upfront listing fees, Unite.AI charges a platform fee only upon the successful sale of a domain. This policy aligns the interests of the platform with those of the sellers, ensuring that Unite.AI is dedicated to facilitating successful transactions. It also provides sellers with confidence, as they are not incurring costs without the guarantee of a sale.

Those interested in selling their domain names can visit the sellers page to learn more about the process.

Conclusion

As the first premium .AI marketplace exclusively serving the AI sector, Unite.AI is at the forefront of digital branding in the AI industry. Whether you’re an entrepreneur looking to launch your AI business or a domain owner seeking to sell, Unite.AI provides a specialized, curated, and strategic platform to meet your needs. It’s more than just a marketplace; it’s a gateway to establishing a formidable presence in the ever-expanding realm of artificial intelligence.

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pandemic-info · 8 months

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Long-Term Long Covid - by Eric Topol

Unfortunately, what was seen at 6 months largely continues out to 2 years.

... [New paper at] Nature Medicine addresses what happened 2 years later to nearly 140,000 people who had Covid, compared with almost 6 million people non-infected controls.

... in the non-hospitalized group a substantial proportion— about 30%— of the 80 sequelae, including GI and neurologic, remained significantly elevated.

... I’d like to point out the data analyzed in this study was enormous, as I tried to capture with one of the supplemental tables below, representative of many others. The authors took on many advanced analytic approaches with weighting, conditional modeling, and sensitivity analyses that I’m not going to review here.

... While this is the first comprehensive and systematic study of Covid at 2 years, it unfortunately is within a highly skewed population. The demographics of nearly 90% men, with a mean age 61 years, is far different than the prototypic person with Long Covid who is more apt to be female and age 30-39 years. Furthermore, to get 2 year follow-up it meant studying a population who had Covid early in the pandemic, before vaccines or the marked evolution of the virus with new variants, including Delta, which was more virulent that the ancestral or Alpha strains that preceded it. So please keep this in mind—the results are important but they may well not be representative of the real world, broader population, of Covid and Long Covid. That’s already a major hole in our knowledge base since there is no other report yet to systematically address a more representative population.

...

Summary

At two years after Covid, there’s a persistent and considerable burden of symptoms and multi-system organ involvement in an important subgroup of people. It’s also unpredictable who will be afflicted with protracted symptoms and new medical diagnoses. While there still is no validated treatment (the Big Miss, as recently reviewed), Long Covid marches on, not just over time for most of those already suffering, but also among newly infected or re-infected individuals — like we are seeing now with increase in cases in the United States and many other countries. The main emphasis here, beyond the enduring and very concerning symptoms and organ dysfunction, is that we are still in the dark. It will take many years to fully know the sequelae of Covid, be it from unforeseen, delayed adverse outcomes like what occurred many years after influenza or polio, or the secondary outcomes of organ systems that are clearly affected, or via promotion of autoimmune conditions or pro-inflammatory pathways, potentially exacerbating risk of atherosclerosis. We’re going to need many more years of careful follow-up to fully understand the ways and extent Covid has hurt us. Meanwhile, beyond the known strategies for prevention of infection, we must consider finding effective ways to treat people who suffer from Long Covid as an urgent and foremost priority.

#long covid #research #data #eric topol #covid #summer 2023 #Ziyad Al-Aly #VA study #nature medicine #sequelae

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