Will AI Slash The Human Workforce?
This question reared its head once again this week as experts debated workplace changes due to AI.
Are We Done With Employing Only Humans?
Imagine using an AI tool to figure if AI tech will eventually change how we work and reduce jobs held by humans? Some (human) experts think everything will stay pretty much the same, while others predict big changes ahead.
AI's rise in content creation and software development is cited as an example of the coming change in other sectors. Will these tools empower humans by automating repetitive tasks, or replace them entirely?
For content creators, gen-AI offers a tool for creating works of art, writing blog posts and articles, even e-books, and so on. Gen-AI can also churn out marketing copy, social media posts, and even write scripts – a content creator's dream for efficiency. Similarly, for programmers, gen-AI holds immense potential. It can automate repetitive coding tasks, suggest optimized code, and even help fix bugs, potentially speeding up software development cycles.
But the tech is like a double-edged sword. It can churn out social media posts and marketing copy at lightning speed, but can it capture the human touch? Gen-AI also holds immense potential to automate repetitive coding tasks, identify bugs, and even suggest optimized solutions. This frees up developers for the truly innovative aspects – crafting elegant solutions, tackling complex problems, and shaping the software's core functionalities.
The future of work perhaps isn't about AI replacing humans; it's about forming powerful partnerships. Developers who embrace gen-AI will become more efficient and versatile, tackling a wider range of projects.
The future belongs to those who can leverage AI's power while harnessing the irreplaceable strengths of human ingenuity. So get ready for a new era of human-AI collaboration, creating groundbreaking solutions across industries.
But before going ahead, let’s look at last week’s AI Jobs Indicator.
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In Today’s Newsletter:
Global Survey Predicts Significant Workforce Reduction Due to Artificial Intelligence
US Tech Job Openings Dip 2% in Q1 2024, Down 47% Since 2022 Peak: Report
Microsoft AI London Hub Will Create Jobs
AI Revolutionizes Investment Banking, Threatening Traditional Tasks and Roles
Texas Schools Implement Automated Grading System for STAAR Exams
AI and Psychometrics Redefine Recruitment
JPMorgan Chase CEO Emphasizes AI's Transformative Impact
New Bill Introduced to Ensure AI Training Transparency
New York Times Investigates AI Companies' Practices Amid Data Acquisition Challenges
Collaboration Between Man And Machine Is Required, Say Experts
AI Investments Overhyped?
New Paper Says AI Models Can Be Taught To Reason
Here Comes A Supercomputer Only For Students
Canada Announces US $1.7bn AI Funding Package
Big Tech’s Rush for Privately-held Data
Two Influential Japanese Companies Call For Urgent AI Legislation
Collaborative AI Agents Boost Performance Significantly, Say Cornell Researchers
Microsoft's Investment in AI in Japan
….plus, TopPicks, Events, and much more.
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Daylight Robbery No More: Big Tech Forced to Pay Up for Data
For years, we've been unwittingly subsidizing Big Tech's empires. We uploaded photos, videos, and our deepest desires onto their platforms, all for "free." Free, of course, came with a hefty price tag: our privacy and, it turns out, a potential fortune.
These tech giants built their billions on the backs of our data, using it to create hyper-targeted advertising and manipulate user behavior. It was a classic case of "finders keepers," with us, the providers, left out in the cold.
Then came the backlash. As the public grew wise to the data game, legal scrutiny mounted. The tide began to turn, particularly in Europe with the implementation of stricter data protection laws. This forced Big Tech to adapt its tactics.
Enter the new gold rush: private data collections. Unable to freely scrape the web anymore, companies like Google and Meta are now lining up to pay for the very content we once freely gave away.
This is a stark reminder: the data we produce has immense value. It's the fuel that powers the AI revolution, and Big Tech is finally starting to acknowledge that.
This new trend of data licensing deals, while a step in the right direction, raises concerns. Are these deals transparent? Does user consent play a role? We must ensure these agreements prioritize user privacy and fair compensation.
The future of AI hinges on ethical data practices. Big Tech must pay for the data it uses, respecting copyright and, more importantly, the rights of the individuals who created it. This isn't daylight robbery anymore; it's a long overdue course correction.
What do you have to say about this? Write in the “Comments” section.
Global Survey Predicts Significant Workforce Reduction Due to Artificial Intelligence
A recent global survey conducted by Swiss staffing firm Adecco Group, in collaboration with research firm Oxford Economics, has shed light on the anticipated impact of artificial intelligence (AI) on the job market. The survey, which polled 2,000 C-suite executives from various industries across nine countries, revealed that a substantial portion of them foresee a decrease in their workforce over the next five years due to the integration of AI technology.
According to the findings, 41% of the executives surveyed expect their companies to employ fewer individuals as a result of AI implementation. This revelation underscores the growing recognition among business leaders of AI's potential to reshape employment dynamics.
Denis Machuel, Chief Executive of Adecco Group, emphasized the transformative nature of AI in the workplace, stating, "AI is emerging as a great disruptor in the world of work." He stressed the importance for companies to prioritize re-skilling and reallocating their teams to effectively navigate this technological shift and mitigate any potential disruptions.
The survey encompassed executives from 18 diverse industries, including energy, retail, and automotive sectors, representing both white-collar and blue-collar job categories. Countries involved in the study included the United States, Canada, Germany, and Japan.
As AI continues to advance, the findings of this survey underscore the pressing need for organizations to adapt their workforce strategies to harness the benefits of technological innovation while minimizing the adverse effects on employment.
Source: cnn.com
Source: adeccogroup
US Tech Job Openings Dip 2% in Q1 2024, Down 47% Since 2022 Peak: Report
According to the debut State of Tech Employment Spring 2024 report, tech job opportunities in the United States saw a 2% decline in the first quarter of 2024, marking a notable decrease of 47% since reaching their peak in April 2022.
On a positive note, AI-related job postings experienced growth during the same period, fueled by heightened demand for professionals skilled in generative AI technologies. Additionally, there was an uptick in the number of job postings related to 5G technology. However, demand for cloud-related expertise saw a quarter-on-quarter decline.
The report also highlighted hiring trends across industries, revealing that the industrial automation sector currently leads in hiring density, surpassing other sectors. Conversely, the telecommunications industry exhibited the lowest hiring density among the industries analyzed.
Source: iot-analytics.com
Microsoft AI London Hub Will Create Jobs
Microsoft is poised to launch its latest endeavor in the realm of artificial intelligence with the inauguration of Microsoft AI London, situated in the vibrant heart of the city.
In the upcoming weeks and months, Microsoft AI will be actively recruiting outstanding individuals to join its team, presenting new employment opportunities in the field of AI.
This new hub is dedicated to spearheading groundbreaking initiatives aimed at propelling the evolution of state-of-the-art language models and their associated infrastructure, alongside the development of cutting-edge tooling for foundational models.
Source: Microsoft
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AI Revolutionizes Investment Banking, Threatening Traditional Tasks and Roles
The traditional rituals of investment banking — burning the midnight oil for PowerPoint presentations, crunching numbers in Excel, and refining intricate financial documents — have long served as rites of passage in the industry. However, the advent of generative artificial intelligence is reshaping this landscape.
Generative AI, renowned for its capacity to generate and analyze vast amounts of data, has now infiltrated Wall Street. Investment banks, historically resistant to cultural shifts, are becoming prime examples of how this technology has the potential not only to augment but also to replace entire cadres of employees.
Source: nytimes.com
Texas Schools Implement Automated Grading System for STAAR Exams, Saving Millions
As students across Texas, USA prepare to take their STAAR exams, they'll be part of a groundbreaking shift in the evaluation process for the state's schools. The Texas Education Agency is introducing an "automated scoring engine" for open-ended questions on the State of Texas Assessment of Academic Readiness (STAAR) in reading, writing, science, and social studies.
This innovative technology, leveraging natural language processing akin to AI chatbots like GPT-4, will automatically grade students' written responses. By implementing this system, the state agency anticipates saving between $15 million to $20 million annually, funds previously allocated for hiring human scorers through third-party contractors.
The decision to integrate this automated scoring method follows the 2023 redesign of the STAAR test, which aimed to provide a more comprehensive assessment of students' comprehension of the state-mandated core curriculum. This redesign notably reduced the number of multiple-choice questions while significantly increasing the inclusion of open-ended questions, referred to as constructed response items. As a result, there are now six to seven times more constructed response items in the STAAR test.
Source: texastribune.org
Transforming Hiring: AI and Psychometrics Redefine Recruitment
In the competitive landscape of corporate recruitment, artificial intelligence and psychometric assessments are revolutionizing the hiring process. From AI-generated resumes to intricate pre-employment screening games, job seekers and employers navigate a new era where technology seeks to quantify the intangible and predict potential. Amidst this digital transformation, questions of bias and fairness loom, challenging the promise of a meritocratic hiring system.
Source: marketplace.org
JPMorgan Chase CEO Emphasizes AI's Transformative Impact
In his annual letter to shareholders, JPMorgan Chase CEO Jamie Dimon highlighted the profound influence of artificial intelligence, foreseeing sweeping changes across business and society at large.
Dimon likened the far-reaching implications of AI to transformative historical innovations such as the printing press, electricity, steam engines, and computers.
He emphasized AI's potential to enhance virtually every role within the company, marking a significant shift in workforce dynamics.
JPMorgan Chase has proactively invested in AI talent, boasting a team of over 2,000 experts and data scientists. Moreover, the firm has successfully implemented over 400 AI and machine learning (ML) use cases.
What It Means For Us
As the leader of one of America's largest financial institutions, Dimon's endorsement of AI's transformative potential carries considerable weight. His letter not only underscores the profound impact of AI but also provides insight into how industry leaders are strategically preparing for a future profoundly shaped by this technology.
New Bill Introduced to Ensure AI Training Transparency
Rep. Adam Schiff (D-Calif.) introduced the "Generative AI Copyright Disclosure Act," which would require companies using copyrighted material to train their AI models to publicly disclose the copyrighted works used. The bill aims to balance innovation with ethical guidelines and protection of creators' rights. It comes amid concerns about the negative impact of AI on artists and content creators, with more than 200 artists calling for responsible AI use. The legislation has garnered support from unions representing actors and writers in Hollywood.
Source: thehill.com
The New York Times Investigates AI Companies' Practices Amid Data Acquisition Challenges
In a recent exposé, The New York Times has delved into the practices of major AI players like OpenAI, Google, and Meta, revealing potential ethical and legal quandaries in their quest to train advanced AI models. The report highlights instances where these companies have reportedly utilized copyrighted materials and transcribed YouTube videos, raising questions about the sources and legality of their training data.
Despite facing legal challenges and accusations of intellectual property theft, these companies have persisted in utilizing copyrighted data for AI training, often without awaiting legal clarification on the matter. Notably, The New York Times itself initiated legal action against Microsoft and OpenAI in December, alleging substantial damages due to the purported "unlawful copying" of its news articles for training GPT models.
In response, OpenAI has argued in a blog post that no single source, including The New York Times, significantly influences the training of its models, indicating a broader reliance on varied data sources.
Source: nytimes.com
This newsletter “All About Content…And AI” is witness to the happenings in the world of content and digital marketing at the intersection of technology…more specifically, AI.
Collaboration Between Man And Machine Is Required, Say Experts
At the recently held "2024 MIT AI Conference", experts discussed the ethical use of AI and the need for governance and regulatory frameworks.
Here’s a summary of the key points regarding "Ethical AI":
Positive-Sum Automation: AI should aim for collaboration between humans and machines, enhancing productivity and satisfaction.Safety and Security: Ethical AI involves safe, secure, humane, and environmentally friendly approaches.
Human-Machine Collaboration: Assessing strengths of humans (context, nuance) versus machines (speed, repetition) is crucial for optimizing collaboration.
Governance and Regulation: The challenge lies in creating appropriate guidelines for AI in academia and business, considering the impact on labor and accuracy.
Industry Adaptation: The necessity for industries to adapt to AI-driven business was noted, with culture change being a critical aspect of this transition.
Overall, the conference underscored the importance of ethical considerations and the collaboration between humans and AI for future advancements.
Source: MIT
AI Investments Overhyped?
François Chollet, a French AI expert, has expressed skepticism about the current hype surrounding generative AI investments, suggesting they are based on false promises.
In an interview, he has emphasized that despite advancements, technologies like GPT-4 are still far from achieving true artificial general intelligence (AGI).
To a question on whether or not, he thought the hopes of investors and tech companies were exaggerated, Francois says there is definitely is a market for generative AI. At the moment the revenue is around 4 billion dollars a year, by 2024 it is expected to be 6 billion. It is a market that is growing rapidly, he says.
The second-most use case of gen-AI is software developers use voice AI to write code, while the most important use so far was students using this tech to do their homework.
But, Francois, adds, the numbers do not seem to add up. In three years, he tells the interviewer, there could be 10 billion in sales, but the growth will soon slow down. The amount of capital invested till then: $90 billion in less than two years.
Source: nzz.ch
New Paper Says AI Models Can Be Taught To Reason
A groundbreaking paper introduces a novel method that takes AI's reasoning abilities to new heights, based on the "Think before you speak" paradigm. This method generates short thoughts after each token, encouraging the Large Language Model (LLM) to quietly engage in internal reasoning processes. Unlike typical outputs, these thoughts are not visible externally but serve to enrich the model's comprehension and predictive capabilities.
The report discusses “Quiet-STaR”, a language model trained on various reasoning tasks from web text to improve reasoning capabilities. It highlights the model's ability to generate meaningful rationales and suggests future directions like ensemble thoughts for better predictions.
The model can predict when thoughts are useful and dynamically allocate compute during generation based on mixing weights. Additionally, the report mentions how generated thoughts can aid in predicting future tokens and the benefits of using a transformer model for interpretability. It also touches on related works in reasoning tasks and plans for specific evaluations of generation quality in the future.
Experimental trials conducted with Mistral 7B demonstrate remarkable enhancements in performance across tasks such as GSM8K and CommonsenseQA. Notably, this approach also showcases promising results in enhancing Chain of Thought reasoning, indicating its broad applicability.
This approach marks a step towards LLMs that can learn to reason in a more general and scalable way, potentially bridging the gap between language model capabilities and human-like reasoning. The research suggests that leveraging language modeling to teach reasoning could lead to more robust and adaptable language models, enhancing their understanding and predictive abilities.
What sets this approach apart is its reliance solely on continued pre-training, without the need for fine-tuning. This distinguishes it from traditional methods and opens avenues for further exploration in machine cognition.
What It Means For Us
The implications of this advancement are profound, prompting speculation about the potential development of machines capable of nuanced thought processes. While the journey towards truly cognitive machines may still be ongoing, this innovation marks a significant step forward in that direction.
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Here Comes A Supercomputer Only For Students
Nvidia and the Georgia Institute of Technology, USA have taken the wraps off the first artificial intelligence(AI) supercomputer tailored for students.
The move is in a bid to democratize access to advanced supercomputing resources typically reserved for tech giants and affiliated startups.
Initially, the computing cluster, powered by Nvidia's enterprise AI software and a bespoke "virtual gateway" crafted by Penguin Solutions, will be exclusively available to undergraduate students at Georgia Tech.
In fact, since the commencement of the semester, students have had the opportunity to utilize the supercomputer in a single class — Foundations of Machine Learning.
However, Georgia Tech aims to expand its usage steadily. Arijit Raychowdhury, chair of Georgia Tech’s School of Electrical and Computer Engineering, revealed in an interview with CNBC that by spring 2025, all undergraduate and graduate students will have access to this resource, underscoring the institution's commitment to embracing AI education at scale.
Source: cnbc.com
Canada Announces US $1.7bn AI Funding Package
Canadian Prime Minister Justin Trudeau has announced a budget allocation of C$2.4 billion ($1.7 bn approx.) for the country's artificial intelligence (AI) sector. The investment aims to enhance Canada's AI capabilities, with a significant portion dedicated to building advanced computing infrastructure for researchers and businesses.
This announcement precedes the upcoming budget presentation and is part of a series of planned spending pledges. Trudeau emphasized the importance of AI investment for economic growth and expressed confidence in Canada's finances.
Source: pymnts.com
Big Tech’s Rush for Privately-held Data
As tech giants face legal and ethical scrutiny over data scraping practices, the industry sees a rush for private collections, with companies like Google, Meta, and Microsoft-backed OpenAI quietly paying for content behind paywalls. The trend signals a major shift as AI model makers seek to mitigate risks and secure data-supply chains through strategic licensing agreements, marking a new era in the race to dominate generative AI technology.
According to this NYT report, one example of this new trend is “Photobucket”, once a leading image-hosting site. It is poised to revitalize its business by entering the generative AI market. CEO Ted Leonard revealed ongoing negotiations to license Photobucket’s extensive archive of 13 billion photos and videos for the training of AI models. This move could potentially unlock billions in content value amidst a burgeoning data market driven by the demand for ‘ethically sourced’ training material.
The report said Photobucket's CEO was discussing rates of between 5 cents and $1 dollar per photo and more than $1 per video, with prices varying widely both by the buyer and the types of imagery sought.
The ongoing negotiations, previously unreported, indicate that the company may possess content worth billions of dollars. This offers a glimpse into the emerging data market driven by the competition to dominate generative AI technology.
"There's currently a race to secure licensing deals with copyright holders who possess private collections inaccessible to web scraping," stated Edward Klaris of Klaris Law, a firm actively advising content owners on substantial deals, each valued in the tens of millions of dollars, to license archives of photos, movies, and books for AI training.
Reuters interviewed over 30 individuals familiar with AI data transactions, including current and former company executives, legal experts, and consultants. This comprehensive investigation provides insight into this nascent market, detailing the types of content being acquired, the prices being negotiated, and emerging concerns regarding the potential inclusion of personal data in AI models without individuals' knowledge or explicit consent.
Source: reuters.com
Two Influential Japanese Companies Call For Urgent AI Legislation
Japan’s largest telecom company, NTT, and the leading newspaper, Yomiuri Shimbun, have called for swift legislation to regulate gen-AI. They warn that without proper control, AI could undermine democracy and social order, potentially leading to wars. NTT and Yomiuri, influential in Japanese policy, have been studying AI’s impact with Keio University researchers, expressing concerns over AI’s moral and accuracy considerations in public discourse.
Source: wsj.com
Collaborative AI Agents Boost Performance Significantly, Say Cornell Researchers
In a groundbreaking study, Cornell researchers have uncovered a powerful method to enhance AI performance collaboration among multiple agents.
The researchers developed numerous AI agents and tasked each with solving a problem independently.
Utilizing a voting system, the agents' responses were amalgamated to determine the optimal solution collectively.
Increasing the number of agents yielded notable improvements in accuracy across various tasks, leveraging diverse Language Model Models (LLMs) such as Llama and GPT.
Interestingly, by scaling up the number of agents, a smaller LLM could match or even surpass the performance of a larger one. For instance, a 13-billion-parameter Llama model surpassed a 70-billion-parameter version on certain tasks.
What It Means For Us
This study underscores a straightforward yet highly effective approach to enhancing AI systems: leveraging the power of collaboration. As computational capabilities continue to advance, the automation of vast numbers of agents for task completion could lead to remarkable advancements in AI capabilities.
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Microsoft's Investment in AI in Japan
The Japanese have kinda been lagging in AI so this could be a boost to their efforts. Microsoft has announced it is investing US $2.9 billion in AI projects in Japan, including infrastructure expansion, AI training, and a new research lab in Tokyo. This marks the company's largest investment in Japan.
The investment will be used for expanding the cloud and AI infrastructure, training 3 million people in AI, and establishing a new Microsoft Research Asia lab in Tokyo. Additionally, Microsoft will collaborate with the Japanese government to enhance cybersecurity resilience.
In addition, Microsoft and the Japanese government will collaborate on strengthening cybersecurity resilience, the report said.
Source: Microsoft
…where every week, I shortlist interesting articles, posts, podcasts, and videos on AI.
Leading 100 AI Tools for Work
This list could be of interest to readers. Daan van Rossum is the founder and CEO of FlexOS and the Author and Host of "Future Work," a newsletter and podcast about a happier future of work.
He has come out with “Top 100 AI For Work Platforms”, which includes the AI tools you should consider adopting to work smarter, not harder.
The Top 10 Gen AI for Work platforms include ChatGPT and Gemini, and also unlikely winners, including Canva at number 3, a platform that went big on AI with images, videos, and presentations. The Austrlia-based design platform shared it had seen 4 billion gen-AI creations on the platforms. Canva grew another 7% in the last two months.
Seven Biggest AI Trends
This article by engineer and manufacturer Stanley Russel explores seven significant AI trends that are reshaping industries and society. These trends include AI-powered automation for streamlining processes and freeing up human capital, the emerging need for explainable AI to foster trust and accountability, the importance of ethical considerations in AI deployment, the integration of AI with IoT at the edge for faster decision-making, AI-powered personalization for tailored experiences, the potential of quantum AI and quantum computing to tackle complex problems, and the increasing role of AI in addressing societal challenges for social good.
Stanley has got it bang on and so I recommend this article as a “must-read”.
The Link
How AI is Affecting Creators
Writer Laura Rosell in her piece titled “The AI Revolution and the Economy Have Killed My Highly-Skilled Job” published in The Writing Cooperative discusses the concerns about AI replacing the specialized work of human academic copyeditors, highlighting the unique skills and value they bring to the research world.
She expresses frustration at the diminishing demand for content services due to AI, leading to economic challenges and burnout within their profession. Laura reflects on the societal implications of AI's impact on livelihoods and emphasizes the need for a world that values and supports human expertise and emotional intelligence.
(A “must-read”, especially for members of the creative tribe struggling in the AI era.)
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