AI and The Future of Work: A Dystopian Vision

This post is based on the book “Machines of Tomorrow: from AI Origins to Superintelligence & Posthumanity”, by Pedro Uria-Recio and Randy McGraw.

INTRODUCTION

Picture a future where the landscape of work is transformed by the relentless advance of AI, where jobs once held by humans are automated into oblivion. In today’s crucial moment, the choices we make about AI development, deployment, and regulation will shape the destiny of work and society. Inspired by the book 'Machines of Tomorrow, by Pedro URIA-RECIO' we delve into the dystopian abyss of the Future of Work, where the promise of utopia fades into uncertainty. But must the Future of Work be shrouded in darkness? Not necessarily. Just last week, we explored a utopian vision where AI catalyzed unprecedented wealth redistribution, offering a more purposeful existence for humanity. Where will the pendulum swing? Likely somewhere in between. This week, our focus shifts to the dystopian side of the spectrum.

As AI and robotics become more sophisticated and capable of handling complex tasks, routine and repetitive jobs will be increasingly automated. The effects in the short-term will be swift and Machiavellian, though somewhat milder than in the medium and longer terms. 

In the short term, most societies’ OS will be able to absorb the shock as the effect is gradual. Exceptions will be found in places like the Philippines, which have economies heavily reliant on easily automatable tasks. For example, more than 25% of the Philippines’ GDP relies on English language and IT-level BPO businesses, and another 25% on overseas remittances from workers who are primarily in at-risk automatable jobs. 

We also recognize that in the short and mid-term, AI has the potential to be a significant job creator, as we discussed in last week’s post. Technology has always created more jobs than it has destroyed, starting with the Neolithic Revolution and extending through the Industrial Revolution. Technology also created net jobs through the mechanization of agriculture during the late 19th and early 20th Centuries and in the IT and Internet explosion starting in the late 1990s.

But we note fundamental differences between the AI revolution and previous turns of the technology screw. Historically, technology has created more jobs than it has destroyed only because three conditions were fully met:

1. Technology allowed humans to do more with fewer resources (e.g., increase productivity), and 

2. The new tools themselves required a thinking human to deploy them, and 

3. The pace of change occurred over decades, enabling educational systems, human retooling, and reskilling to adjust, or in some cases, for children to learn the new skills relevant to the new technologies.

With the current and coming economic environment guided by AI and robotics, each of these factors has a different configuration: 

1. The locus of productivity is migrating up the value chain to increasingly higher levels of judgment, with fewer humans needed to generate higher productivity.

2. The technology itself, particularly advanced Artificial General Intelligence (AGI), will gradually replace human thinking.

3. The pace of change is outstripping the ability to retrain programs and individuals to keep up, with most people not even knowing “where to start.” In the last technological revolution, an internet firewall or other IT product, for example, did not improve faster than human capability to learn and manage it; however, that is already not the case with AI.

Worse still, societies are aging, but rapid, high-complexity technical reskilling favors the young. Thus, an increasingly larger number of people will be either unwilling or incapable of learning and adapting fast enough. Punctuating the ill effect, AI itself learns faster than all humans do.

We believe that none of these conditions is apt to become favorable over the long term. The migration of productivity to higher levels of judgment in decision-making has already started and will creep along unrelentingly as algorithms improve. As the speed of change accelerates and the level of intelligence of AI systems increases toward AGI, it will turn into a permanent net destructor of jobs. 

Over time, we believe most people everywhere will be permanently displaced, with certain jobs gone to AI and never coming back. Fears of widespread unemployment, particularly in sectors heavily reliant on manual labor, low-level creative, and routine tasks, are well-founded and will accelerate as AI is more widely deployed. 

The only real questions are: what will the pace be, and consequently, what is the adjustment mechanism deployed within a society's OS, and ultimately what happens to the concept of work itself? 

The effect of economic displacement will cascade. In this dystopian view, people will be forced back to multi-generational living, possibly even communal living. Resources available for travel and leisure will be limited, perhaps even doled out in ways tied to perpetuating political power. And the Government will extend its reach further into the lives of individuals. Concepts such as “you'll own nothing and be happy” originated in a 2016 video by the WEF, and alongside “fractional ownership of your living accommodation” —concepts already growing louder in Western societies—only portends this outcome, a mass grooming exercise. The population will shrink as the ability to afford children beyond replacement level in society will become a luxury (perhaps through purchasing licenses to procreate) as the Economic Value of Human Life will mathematically decline since GDP per capita can actually increase geometrically with a shrinking human population. The authoritarian socialist Government will double down on its self-appointed need to be redistributionist, allocating the best spoils via licensing and other mechanisms to itself and its political supporters and UBI as a form of sufficient living, perhaps only to those who support them.

While it will take decades to completely activate, AI could potentially lead to the complete automation of human labor. We see the eradication of work structured in five stages that run sequentially but with significant overlaps: 

1. The first stage of AI-induced unemployment involves the automation of routine, rule-based, standardized, and repetitive tasks, leading to the displacement of workers in roles such as data entry, customer service, and routine manufacturing. This is already underway through Robotic Process Automation (RPA).

2. The second stage involves the integration of AI into creative processes, impacting jobs that require cognitive skills, pattern recognition, and creativity. Professions such as graphic design, marketing, non-CPA accounting, and sub-partner level legal (paralegals, drafters, brief preparers) may witness significant changes. This process is also underway through Generative AI.

3. The third stage sees mass adoption of autonomous systems and advanced robotics, intensifying the impact on the job market. Industries such as transportation, delivery services, and even jobs that require an empathetic touch, such as elderly care, will witness the displacement of human workers. The first place where this is already happening is in Japan, where automation is seen as an alternative to immigration. For example, Amazon has started experiments with drone delivery and robotic warehouse work. We also note the robot baristas that have been experimented with even in relatively low labor cost markets.

4. The fourth stage marks a shift towards the automation of tasks that involve higher-level causal analysis. This includes jobs in finance, research, engineering, medicine, and even creative fields, challenging the notion that certain professions are immune to automation. This phase has not started because AGI would be necessary.

5. In the fifth and final stage, AI becomes deeply integrated into all facets of society, even those involving deep interpersonal relations. Virtually every industry, from education to healthcare, experiences a significant presence of AI-driven systems at all but the highest ownership or judgment levels. The fundamental change to society's OS is complete, with new economic models, human interaction models against, and ultimately, a new culture. 

After these five stages, most jobs and economic activities will be automated, rendering human beings non-competitive in the workforce. We note that there are likely to be five categories of individuals at this juncture: 

1. Those who own resources and choose to manage them themselves—this group will include the so-called “superstars,” the owners of capital and existing production means. 

2. Those who administer the political processes—this includes Government officials who add no value but are absorbed into the Government structure.

3. Those who engage in activities solely for personal enjoyment—this group encompasses entrepreneurs who derive satisfaction from creating companies or enjoying complete independence, as well as artists who find fulfillment in expressing themselves through their art even in the absence of economic benefit. 

4. Those who primarily engage in sports—enhanced humans and cyborgs. 

5. Those who literally do nothing but consume—the vast majority of humankind. 

In reference to this last group, during the AI Safety Summit in Bletchley Park, UK, in November 2023, Rishi Sunak, the UK prime minister, asked Elon Musk about the impact of AI on employment. Musk forecasted that human labor might become obsolete: “I think we are seeing the most disruptive force in history here[...] There will come a point where no job is needed. You can have a job if you want to have a job for personal satisfaction, but the AI will be able to do everything. “Perhaps you ask, “How is this final result dystopian?” With consumption perfectly fungible as an activity, those who only consume will likewise become fungible and replaceable in the broader context of the system.

In the previous week, we introduced the concept of Universal Basic Income (UBI) to offset AI-driven economic dislocation, an idea gaining traction in political and economic discussions. UBI is proposed to provide all citizens with a regular, unconditional sum of money. 

Advocates of UBI argue that it can alleviate poverty, enhance social welfare, and empower individuals. However, a closer examination reveals the potential for UBI to be employed as a tool for mass control, influencing the behavior and sentiments of the populace, with no guarantee that the wealth created by AI efficiencies will ever reach people at all, let alone in a fair way.

UBI generates many dystopian-leaning concerns. The first concern is the creation of economic dependency among recipients and where that leads at scale. By establishing a continuous flow of financial support with no requirements to receipt, increasing swathes of individuals may become reliant on the state for their sustenance. This dependency can easily be leveraged by those in power, both Governments and the oligopolies they protect, to subtly manipulate the masses, fostering a sense of gratitude and loyalty to the governing authority. AI is a technology that can aid absolutism to an overpowering degree.

Second, Governments with an objective of power and control could predictably manipulate UBI eligibility requirements and amounts disbursed to influence voting behavior or engage in social engineering, making elections a formality and a sham. By adjusting UBI levels based on political allegiance or compliance or controlling access to licensing to conduct activities under AI, those in power can easily shape the political landscape, punishing those who have a different opinion or whoever they want, based on their own visions of social engineering. This would likely take the form of quelling dissent and discouraging resistance, creating a population more amenable to, and perhaps even happy with, authoritarian socialism. It would likely contribute to cultural homogenization, with the new societal OS being solely defined by who owns and programs the algorithms. In short, UBI could lead to a society less inclined to challenge authority or question the status quo, which is not good for democracy. The government-controlled educational system will aid and abet it. There is nothing you will be able to do about it. Even on paper, Western Governments will transform from being in the employ of the people to becoming rulers over the people, with the US itself risking full reversion to pre-1776 forms of Aristocratic Rule. 

Third, people acting in their own self-interest will take whatever Faustian Bargain is thrown at them, with the fear of losing their financial lifeline, ensuring conformity to societal norms and Government directives. The actual implementation of UBI provides a further case in point. It involves a sophisticated system of financial transactions and monitoring, which renders it, at core, a vast surveillance infrastructure, allowing authorities to track and analyze the spending habits of individuals—rejecting spending it does not want and using the data to feed algorithms that further strengthen its ability to control you. This data could also be exploited to identify dissenters or individuals with anti-establishment views, enabling preemptive measures to be taken to maintain control. 

Proponents argue that UBI could encourage entrepreneurship and creativity by providing a safety net. Even if that were true, there is also an omnipresent risk at the margin of reduced motivation and productivity, with the percentage of the population that sits on the inside of the margin a function of the level of UBI and rules of access set by the Government. This effect is independent of other elements of UBI. 

One of the reasons why many of the “AI superstars” and current Western politicians are supportive of UBI is because it is a continuation of the current expansive monetary policies where central banks are printing money. That money is getting disproportionately concentrated in the hands of the AI superstars, who own an increasing share of valuable non-currency-based assets, e.g., company ownership or assets that produce something. Further, this makes the fiat or digital currency less valuable while at the same time making the assets of product and service creation and distribution increasingly more valuable. One way of implementing UBI would be redirecting a combination of newly printed money and increased taxes into UBI subsidies. People would use those UBI subsidies to continue buying the products and services created by the AI superstars. This way, they would continue increasing their concentration of assets while most of the population has no assets and relies on monthly subsidies. 

Although it might sound contradictory, one of the most effective ways to promote human employment would actually be not providing UBI. If companies start replacing people with robots in a massive way and unemployment reaches a very significant share of the population, there would no longer be clients to buy the products of those companies. They would have to scale up employment in any case. This is similar to Henry Ford's reasoning for paying employees well enough so that they could afford a car. From a free-market perspective, markets have self-correction mechanisms that allow them to self-regulate and make sure unemployment does not reach the kind of level that AGI could take it to if left unchecked. For libertarians, it is precisely market interventions like UBI, which, although well-intentioned, end up creating both economic and spiritual poverty.

This post is based on the book “Machines of Tomorrow: from AI Origins to Superintelligence & Posthumanity”, by Pedro Uria-Recio and Randy McGraw.

TheGen.AI News

Gartner Forecasts $50 Billion Market by 2027 Driven by Generative AI

The legal technology market is poised for rapid expansion, with projections indicating it could reach a $50 billion valuation by 2027, fueled by advancements in generative AI (GenAI), according to Gartner, Inc.

Chris Audet, Chief of Research at Gartner for Legal, Risk & Compliance Leaders, highlights the transformative role of GenAI in legal technologies. He notes that the evolution of GenAI, along with the accessibility of consumer tools like OpenAI's ChatGPT and Google's Bard, is set to broaden the application of established legal technologies, thus driving market growth.

There has been notable investment in areas such as spend management, e-billing, contract lifecycle management, legal matter management, and legal document management. The integration of GenAI into these systems is expected to further boost their adoption and efficiency.

For legal departments, the imperative is clear: embrace emerging technologies to meet business needs and mitigate future budget constraints. Audet emphasizes the importance for legal leaders to assess the potential of GenAI to respond proactively to automation trends across various business functions.

Equally crucial is the need for lawyers to grasp both the capabilities and limitations of GenAI. Rigorous scrutiny of GenAI outputs is essential, as the technology is not yet reliable for unsupervised task execution.

The adoption of GenAI is likely to necessitate significant adjustments within legal departments and payment structures. Issues such as tracking billable hours when documents are AI-assisted, and the changing needs for legal services, counsel expenses, and lawyer specialization are anticipated challenges that may drive organizational changes.

Audet asserts that while new technologies like GenAI may initially overpromise, their long-term success often hinges on adapting to new operational methods rather than on the technologies' inherent flaws.

Further details are discussed in Gartner's report, "Predicts 2024: The Transformative Impact of Generative AI on Legal Technologies."

70% Embrace GenAI at Work, But Only 43% See Its Daily Benefits

ChatGPT quickly became a phenomenon, reaching one million users in just five days and epitomizing the public's strong interest in artificial intelligence, as revealed by a Boston Consulting Group (BCG) study.

The report, titled "Consumers Know More About AI than Business Leaders Think," is based on a survey by BCG's Center for Customer Insight, involving 21,000 people from 21 countries. It assesses awareness, use, and attitudes towards AI and generative AI (GenAI), as well as its workplace implications.

Aparna Bharadwaj, global leader of BCG’s Global Advantage practice, points out that consumer understanding of AI is more profound than many business leaders assume. She stresses the importance of adopting responsible AI practices to address consumer and employee concerns about data privacy and ethical issues, which are essential for wider acceptance of the technology.

Key findings include:

- Over 80% of respondents are aware of GenAI, with a quarter having used it.

- Three-quarters have utilized GenAI-powered apps or services, with under-35s showing higher engagement than older groups.

- There's a "misinformation-excitement-concern curve" associated with AI. Initial fears due to misinformation give way to excitement and concern as people gain more experience with GenAI.

Consumers express mixed feelings:

- 40% are excited about AI's possibilities.

- 28% feel conflicted about AI.

- 33% worry about data security and ethical issues.

- 30% are concerned about AI replacing jobs.

- 10% are anxious about the environmental impacts of GenAI.

Regarding AI's potential in the workplace:

- 70% of employees are optimistic about using GenAI.

- Many believe AI will enhance learning, education, and workplace efficiency.

- Perceptions vary by job role, with process-intensive roles feeling more threatened by AI than those in relationship-intensive roles.

Sentiments about AI differ globally. Countries like China, Indonesia, and Brazil show high excitement, whereas France, Australia, and the UK express significant concerns. Younger, more digitally proficient populations tend to be more enthusiastic, while digitally competitive economies show higher levels of concern.

Implications for leaders include:

- Emphasize transparency and address privacy proactively when introducing new AI applications.

- Tailor approaches to different markets, focusing on regions more receptive to AI.

- Manage the pace of scaling AI solutions to maintain consumer trust.

- Recognize the importance of people and processes, adhering to the 10-20-70 rule: 10% algorithm development, 20% tech deployment, 70% change management.

Jessica Apotheker, BCG’s chief marketing officer, emphasizes the need for leaders to build trust by respecting consumer perceptions and intelligently navigating the complex sentiment landscape surrounding AI.

Gen Z Prefers Generative AI for Career Advice Over Traditional Managers

A recent survey by an outplacement services firm has revealed that nearly half of Gen Z employees prefer receiving career advice from AI chatbots like ChatGPT over their managers, citing a lack of support for their career development. The study, conducted with Workplace Intelligence, highlights broader issues such as toxic work environments and limited upward mobility as key factors contributing to employee dissatisfaction.

The research found that 47% of Gen Z workers feel they receive better career guidance from chatbots than from their managers. This trend is attributed to inadequate corporate learning and development programs and the challenges of building professional networks in predominantly hybrid work settings. Lydia Frank, vice president of marketing at Chronus, notes that Gen Z's familiarity with digital solutions drives their preference for AI-based career coaching.

The survey also revealed widespread concerns about workplace toxicity, with 77% of all employees and 79% of HR leaders acknowledging exposure to toxic work traits. Key issues include managerial favoritism and a disregard for employee feedback, which 46% and 42% of employees, respectively, identified as major problems.

Furthermore, a significant portion of employees reported receiving poor career advice from their managers, with many turning to friends, family, and online resources for better guidance. According to the survey, 63% of employees believe their employers prioritize productivity over career development, and 54% feel neglected by their organizations regarding career growth.

These workplace challenges are prompting a high turnover rate, with HR leaders predicting that 25% of employees are likely to resign within the next six months due to insufficient career development support. This sentiment is even more pronounced among Gen Z employees, 44% of whom are expected to quit for the same reasons.

The findings underscore the urgent need for organizations to prioritize effective career development strategies to retain talent and enhance job satisfaction.

TheOpen.AI News

How AI is Fueling Microsoft and Google's Financial Success?

Google and Microsoft have recently demonstrated strong financial results, with significant profit increases largely attributed to their substantial investments in artificial intelligence (AI). Alphabet, Google's parent company, reported a remarkable 57 percent rise in profits, reaching $23.7 billion for the first quarter of the year. This surge in earnings led to a notable 11 percent increase in their stock value in after-market trading. In a historic move, Alphabet also declared its first-ever dividend, set at $0.20 per share.

Sundar Pichai, Google’s CEO, credited the success to advancements in AI, particularly highlighting the impact of their AI text-to-image model, Gemini. Pichai emphasized Google's strong position in AI research and global product offerings as key factors setting the stage for future innovations.

Microsoft also posted impressive results with a 20 percent increase in quarterly profits, amounting to $21.93 billion. This financial success pushed their shares up by 4 percent in after-market trades.

These positive outcomes contrast sharply with Meta, the parent company of Facebook and Instagram, which saw a drastic $200 billion loss in market value. This decline occurred after CEO Mark Zuckerberg cautioned about rising expenses linked to AI investments.

Amidst these financial disclosures, regulatory scrutiny continues to intensify. Both in the United States and Europe, authorities are examining the competitive impacts and potential risks associated with AI. The U.S. Federal Trade Commission initiated an investigation in January into the multibillion-dollar partnerships between leading tech giants like Microsoft, Amazon, Google, and AI startups such as OpenAI and Anthropic, assessing their effects on market competition. Furthermore, in March, the European Commission launched a probe focusing on how these tech companies manage risks related to AI, including issues like computer-generated deepfakes. These regulatory moves highlight the growing concerns and attention AI technologies are drawing on a global scale.

Microsoft's AI Advances Challenge Amazon's Cloud Dominance

As U.S. tech giants gear up for their quarterly earnings reports, there's growing anticipation that Microsoft may be narrowing the gap with cloud-computing market leader Amazon.com. This shift is attributed to businesses increasingly migrating to Microsoft's services, drawn by a suite of generative AI features powered by OpenAI technology.

Microsoft, headquartered in Redmond, Washington, introduced its AI-driven Copilot for business applications in November, priced at $30 per month. This toolset has positioned Microsoft ahead of its competitors, Amazon and Google's Alphabet, in deploying generative AI services. The upcoming earnings report on Thursday will serve as a significant indicator of AI adoption levels and could influence tech stock movements, particularly as the sector has seen some cooling off amid concerns about prolonged high U.S. interest rates.

Wall Street analysts are optimistic about Microsoft, which surpassed Apple as the world's most valuable company earlier this year, anticipating that its substantial investments in generative AI are paying off by attracting more clients to its Azure cloud-computing platform. Rishi Jaluria from RBC Capital Markets commented on the "halo effect" around Microsoft’s AI strategy, suggesting it could enable Microsoft to capture market share from Amazon. He also noted that cloud providers might benefit from a stabilization in technology spending, which has recently been under pressure due to high-interest rates and economic uncertainties.

For the first quarter of 2024, projections suggest that Microsoft’s revenue grew by 15% and Alphabet’s by 12.6%, marking their second-highest growth rate in nearly two years. Amazon's revenue is expected to increase by 11.9%, representing its lowest growth in three quarters. Within Microsoft, the Intelligent Cloud unit, which includes Azure, is forecasted to have expanded by 28.9% during the January-to-March period, compared to Amazon Web Services' growth of 14.9% and Google Cloud's 25%.

CFRA Research analyst Angelo Zino estimated that up to 8 percentage points of Azure’s growth could be attributed to its AI services. However, the full potential of AI-driven growth is anticipated to materialize from next year onwards, with Morgan Stanley analysts estimating a $5 billion revenue contribution from Copilot in Microsoft's fiscal year 2025, which begins in July.

Conversely, while Alphabet has seen its shares rise by over 13% this year, fueled by optimism about its AI initiatives like the Gemini models, the monetization of these technologies is not being rushed. Alphabet offers AI features in its Workspace productivity apps, along with two $10 add-on packages introduced this month for AI meeting notes, summaries, and enhanced security features. Despite the high interest observed at the Google Cloud Next conference, analysts from Jefferies noted that there is no hurried push to transition AI pilots into production apps, anticipating a more significant impact in 2025.

TCS CEO K Krithivasan Warns of Risk to Call Center Roles

Tata Consultancy Services (TCS) CEO K Krithivasan has projected a significant transformation in the call center industry due to the integration of Artificial Intelligence (AI), particularly generative AI. In a recent interview with Financial Times, Krithivasan discussed how AI is set to revolutionize customer service operations in Asia and globally, predicting a shift towards AI systems that can proactively resolve customer issues before they escalate into calls.

Krithivasan envisions a near future where traditional incoming call centers are largely redundant, as AI technologies advance to predict and preemptively address customer inquiries. He anticipates that within the next year, developments in chatbot technology will allow these systems to analyze customer transaction histories and manage tasks that human agents currently handle. Yet, he cautions that this shift might not happen overnight and that the true impact of generative AI will unfold gradually.

While there is considerable excitement about the potential of generative AI, Krithivasan suggests tempering immediate expectations. He acknowledges the discourse surrounding AI but points out that its significant effects will take time to manifest. Interestingly, he posits that AI may create new job opportunities rather than merely displacing existing ones.

Addressing concerns regarding potential job losses, Krithivasan remains optimistic about the demand for technology talent, especially in India. He argues that the evolution of AI could lead to more skilled job creation, thus offsetting the risk of job contraction.

Conversely, a report by the McKinsey Global Institute, titled "Generative AI and the Future of Work in America," paints a different picture, highlighting the automation of roles that involve repetitive tasks, data collection, and basic data processing. According to this report, significant job reductions are expected in sectors like office support, customer service, and food service. Specific predictions include a reduction of 1.6 million jobs for clerks, along with notable decreases in positions for retail salespersons, administrative assistants, and cashiers. These sectors are particularly vulnerable due to the high proportion of automatable activities within their job scopes.

Together, these insights from Krithivasan and the McKinsey report illustrate the dual-edged nature of AI's impact on the workforce: while AI promises efficiency and new capabilities, it also poses challenges for traditional employment structures, necessitating thoughtful strategies to manage the transition and mitigate potential adverse effects on workers.

TheClosed.AI News

NVIDIA CEO Jensen Huang Personally Delivers DGX H200 to OpenAI

NVIDIA's CEO Jensen Huang recently delivered the first NVIDIA DGX H200 directly to OpenAI, an event highlighted by Greg Brockman, OpenAI's president, on social media. The handover symbolizes a continuing partnership, as this gesture echoes a similar one from 2016 when Huang donated the first DGX-1 AI supercomputer to OpenAI, an event acknowledged by then active supporter Elon Musk.

The DGX H200, an advancement over the previous H100 model, features substantial upgrades that enhance its capacity to handle the intensive demands of generative AI. It offers 1.4 times more memory bandwidth and 1.8 times more memory capacity than its predecessor. The memory itself is upgraded to HBM3e, pushing the bandwidth up to 4.8 terabytes per second and increasing the total memory to 141GB. These improvements make the H200 particularly suited for large-scale AI tasks, including the development of GPT-5 and the deployment of Sora, both OpenAI projects slated for advancement this year.

Ian Buck, NVIDIA’s VP of hyperscale and HPC, emphasized the importance of such high-capacity and high-speed resources in developing generative AI and handling high-performance computing applications. The DGX H200 is part of NVIDIA's AI supercomputing platform, which now includes the use of NVLink technology to integrate 256 H200 superchips into a single unit, achieving 1 exaflop of performance and offering 144 terabytes of shared memory. This represents a significant upgrade over the DGX A100, introduced in 2020, marking a new era in AI-driven computational power.

OpenAI Unveils New Security and Cost Management Tools for Business Users

OpenAI has introduced a new "Projects" feature, providing organizations with more refined administrative control over their use of OpenAI's services. This feature allows for detailed management of roles and API keys specific to individual projects, alongside the capability to customize model accessibility and set precise usage and rate limits to prevent unexpected cost overruns. Additionally, project owners can now generate service account API keys, which provide project access without being linked to a specific user's account.

In addition to the Projects feature, OpenAI has rolled out several enhancements to its Assistants API. These improvements aim to offer better accuracy in data retrieval, increased flexibility in model behavior, and enhanced cost management tools. Notably, the 'file_search' capability has been significantly upgraded to handle up to 10,000 files per assistant, a massive increase from the previous limit of 20 files. This tool now supports faster, parallel queries through multi-threaded searches and has improved features for reranking and query rewriting.

Further updates include the introduction of streaming support for real-time, conversational responses, a highly requested feature from developers and businesses. OpenAI has also integrated 'vector_store' objects, allowing users to add, automatically parse, chunk, and embed files for enhanced search capabilities. These vector stores are sharable across assistants and threads, simplifying file management and billing processes.

OpenAI now allows users to control the maximum number of tokens used per run and set limits on the number of previous and recent messages considered in each session, helping manage the costs associated with token usage. The new 'tool_choice' parameter enables users to select specific tools like 'file_search', 'code_interpreter', or 'function' for each run, and there is now support for fine-tuned GPT-3.5 Turbo models within the API.

To further assist businesses in managing expenses, OpenAI offers sustained levels of tokens per minute (TPM) usage on GPT-4 or GPT-4 Turbo, with discounts ranging from 10–50% based on usage commitment. Additionally, the newly introduced Batch API supports asynchronous processing of non-urgent workloads at 50% off the usual price, ideal for tasks such as model evaluation, offline classification, summarization, and synthetic data generation, with results returned within 24 hours.

Sam Altman's Worldcoin in Talks for Partnerships with PayPal and OpenAI

Tools for Humanity, the organization behind Sam Altman's iris-scanning initiative Worldcoin, is exploring potential collaborations with industry giants PayPal and OpenAI, as reported by Bloomberg. Alex Blania, CEO of Tools for Humanity, discussed these possible partnerships, though specific details or formal agreements have yet to be disclosed.

Previously, the company successfully partnered with cybersecurity firm Okta to develop an authentication service, demonstrating its capability and willingness to collaborate with established industry players.

Worldcoin's Vision and Challenges

Worldcoin aims to be a free, privacy-centric, open protocol that could evolve into the world's largest identity and financial public network. The project leverages unique iris-scanning technology to authenticate users' "humanness" amidst growing concerns over automation and digital impersonation. By scanning their irises, users can transform their biometric data into encrypted numerical strings, ensuring secure identity verification. Participants are incentivized with Worldcoin tokens, valued at approximately $5, for engaging in the scanning process.

However, Worldcoin has encountered several challenges, including data privacy concerns and regulatory hurdles, particularly in European and African countries. These issues have contributed to fluctuations in the company's token market cap.

In response to these challenges and to broaden its reach, the Worldcoin Foundation recently unveiled plans for World Chain, a permissionless, open-source layer-2 blockchain slated for launch in mid-2024. This new blockchain is designed to integrate more closely with the Worldcoin protocol and further incentivize users by providing a World ID.

Strategic Partnerships and Future Outlook

The potential collaborations with PayPal and OpenAI would mark significant strides for Worldcoin in establishing itself at the nexus of identity verification and fintech. These partnerships could enhance Worldcoin's technological capabilities and market presence.

Despite the hurdles it faces, Tools for Humanity remains committed to its vision of crafting a secure, decentralized identity and financial network, driving forward with its innovative approach to blending technology with user incentives. The company's ongoing efforts to forge strategic partnerships underscore its dedication to innovation and collaboration in the evolving landscape of digital identity and blockchain technology.

Join the movement - If you wish to contribute thought leadership, then please fill the form below. One of our team members will be back in touch with you shortly.

Form link

Keep reading