Connect with us


The Biggest Ethical Concerns in the Future of AI – ReadWrite



Nate Nead

Artificial intelligence (AI) is rapidly improving, becoming an embedded feature of almost any type of software platform you can imagine, and serving as the foundation for countless types of digital assistants. It’s used in everything from data analytics and pattern recognition to automation and speech replication. 

The potential of this technology has sparked imaginative minds for decades, inspiring science fiction authors, entrepreneurs, and everyone in between to speculate about what an AI-driven future could look like. But as we get nearer and nearer to a hypothetical technological singularity, there are some ethical concerns we need to keep in mind. 

Unemployment and Job Availability 

Up first is the problem of unemployment. AI certainly has the power to automate tasks that were once capable of completion only with manual human effort. 

At one extreme, experts argue that this could one day be devastating for our economy and human wellbeing; AI could become so advanced and so prevalent that it replaces the majority of human jobs. This would lead to record unemployment numbers, which could tank the economy and lead to widespread depression—and, subsequently, other problems like crime rates. 

At the other extreme, experts argue that AI will mostly change jobs that already exist; rather than replacing jobs, AI would enhance them, giving people an opportunity to improve their skillsets and advance. 

The ethical dilemma here largely rests with employers. If you could leverage AI to replace a human being, it would increase efficiency and reduce costs, while possibly improving safety as well, would you do it? Doing so seems like the logical move, but at scale, lots of businesses making these types of decisions could have dangerous consequences. 

Technology Access and Wealth Inequality

We also need to think about the accessibility of AI technology, and its potential effects on wealth inequality in the future. Currently, the entities with the most advanced AI tend to be big tech companies and wealthy individuals. Google, for example, leverages AI for its traditional business operations, including software development as well as experimental novelties—like beating the world’s best Go player. 

AI has the power to greatly improve productive capacity, innovation, and even creativity. Whoever has access to the most advanced AI will have an immense and ever-growing advantage over people with inferior access. Given that only the wealthiest people and most powerful companies will have access to the most powerful AI, this will almost certainly make the wealth and power gaps that already exist much stronger. 

But what’s the alternative? Should there be an authority to dole out access to AI? If so, who should make these decisions? The answer isn’t so simple. 

What It Means to Be Human

Using AI to modify human intelligence or change how humans interact would also require us to consider what it means to be human. If a human being demonstrates an intellectual feat with the help of an implanted AI chip, can we still consider it a human feat? If we heavily rely on AI interactions rather than human interactions for our daily needs, what kind of effect would it have on our mood and wellbeing? Should we change our approach to AI to avoid this? 

The Paperclip Maximizer and Other Problems of AI Being “Too Good”

One of the most familiar problems in AI is its potential to be “too good.” Essentially, this means the AI is incredibly powerful and designed to do a specific task, but its performance has unforeseen consequences. 

The thought experiment commonly cited to explore this idea is the “paperclip maximizer,” an AI designed to make paperclips as efficiently as possible. This machine’s only purpose is to make paperclips, so if left to its own devices, it may start making paperclips out of finite material resources, eventually exhausting the planet. And if you try to turn it off, it may stop you—since you’re getting in the way of its only function, making paperclips. The machine isn’t malevolent or even conscious, but capable of highly destructive actions. 

This dilemma is made even more complicated by the fact that most programmers won’t know the holes in their own programming until its too late. Currently, no regulatory body can dictate how AI must be programmed to avoid such catastrophes because the problem is, by definition, invisible. Should we continue pushing the limits of AI regardless? Or slow our momentum until we can better address this issue? 

Bias and Uneven Benefits 

As we use rudimentary forms of AI in our daily life, we’re becoming increasingly aware of the biases lurking within their coding. Conversational AI, facial recognition algorithms, and even search engines were largely designed by similar demographics, and therefore ignore the problems faced by other demographics. For example, facial recognition systems may be better at recognizing white faces than the faces of minority populations. 

Again, who is going to be responsible for solving this problem? A more diverse workforce of programmers could potentially counteract these effects, but is this a guarantee? And if so, how would you enforce such a policy? 

Privacy and Security 

Consumers are also growing increasingly concerned about their privacy and security when it comes to AI, and for good reason. Today’s tech consumers are getting used to having devices and software constantly involved in their lives; their smartphones, smart speakers, and other devices are always listening and gathering data on them. Every action you take on the web, from checking a social media app to searching for a product, is logged. 

On the surface, this may not seem like much of an issue. But if powerful AI is in the wrong hands, it could easily be exploited. A sufficiently motivated individual, company, or rogue hacker could leverage AI to learn about potential targets and attack them—or else use their information for nefarious purposes. 

The Evil Genius Problem 

Speaking of nefarious purposes, another ethical concern in the AI world is the “evil genius” problem. In other words, what controls can we put in place to prevent powerful AI from getting in the hands of an “evil genius,” and who should be responsible for those controls? 

This problem is similar to the problem with nuclear weapons. If even one “evil” person gets access to these technologies, they could do untold damage to the world. The best recommended solution for nuclear weapons has been disarmament, or limiting the number of weapons currently available, on all sides. But AI would be much more difficult to control—plus, we’d be missing out on all the potential benefits of AI by limiting its progression. 

AI Rights 

Science fiction authors like to imagine a world where AI is so complex that it’s practically indistinguishable from human intelligence. Experts debate whether this is possible, but let’s assume it is. Would it be in our best interests to treat this AI like a “true” form of intelligence? Would that mean it has the same rights as a human being? 

This opens the door to a large subset of ethical considerations. For example, it calls back to our question on “what it means to be human,” and forces us to consider whether shutting down a machine could someday qualify as murder. 

Of all the ethical considerations on this list, this is one of the most far-off. We’re nowhere near territory that could make AI seem like human-level intelligence. 

The Technological Singularity 

There’s also the prospect of the technological singularity—the point at which AI becomes so powerful that it surpasses human intelligence in every conceivable way, doing more than simply replacing some functions that have been traditionally very manual. When this happens, AI would conceivably be able to improve itself—and operate without human intervention. 

What would this mean for the future? Could we ever be confident that this machine will operate with humanity’s best interests in mind? Would the best course of action be avoiding this level of advancement at all costs? 

There isn’t a clear answer for any of these ethical dilemmas, which is why they remain such powerful and important dilemmas to consider. If we’re going to continue advancing technologically while remaining a safe, ethical, and productive culture, we need to take these concerns seriously as we continue making progress. 

Nate Nead

Nate Nead is the CEO & Managing Member of Nead, LLC, a consulting company that provides strategic advisory services across multiple disciplines including finance, marketing and software development. For over a decade Nate had provided strategic guidance on M&A, capital procurement, technology and marketing solutions for some of the most well-known online brands. He and his team advise Fortune 500 and SMB clients alike. The team is based in Seattle, Washington; El Paso, Texas and West Palm Beach, Florida.


Fintech Kennek raises $12.5M seed round to digitize lending



Google eyed for $2 billion Anthropic deal after major Amazon play

London-based fintech startup Kennek has raised $12.5 million in seed funding to expand its lending operating system.

According to an Oct. 10 report, the round was led by HV Capital and included participation from Dutch Founders Fund, AlbionVC, FFVC, Plug & Play Ventures, and Syndicate One. Kennek offers software-as-a-service tools to help non-bank lenders streamline their operations using open banking, open finance, and payments.

The platform aims to automate time-consuming manual tasks and consolidate fragmented data to simplify lending. Xavier De Pauw, founder of Kennek said:

“Until kennek, lenders had to devote countless hours to menial operational tasks and deal with jumbled and hard-coded data – which makes every other part of lending a headache. As former lenders ourselves, we lived and breathed these frustrations, and built kennek to make them a thing of the past.”

The company said the latest funding round was oversubscribed and closed quickly despite the challenging fundraising environment. The new capital will be used to expand Kennek’s engineering team and strengthen its market position in the UK while exploring expansion into other European markets. Barbod Namini, Partner at lead investor HV Capital, commented on the investment:

“Kennek has developed an ambitious and genuinely unique proposition which we think can be the foundation of the entire alternative lending space. […] It is a complicated market and a solution that brings together all information and stakeholders onto a single platform is highly compelling for both lenders & the ecosystem as a whole.”

The fintech lending space has grown rapidly in recent years, but many lenders still rely on legacy systems and manual processes that limit efficiency and scalability. Kennek aims to leverage open banking and data integration to provide lenders with a more streamlined, automated lending experience.

The seed funding will allow the London-based startup to continue developing its platform and expanding its team to meet demand from non-bank lenders looking to digitize operations. Kennek’s focus on the UK and Europe also comes amid rising adoption of open banking and open finance in the regions.

Featured Image Credit: Photo from; Thank you!

Radek Zielinski

Radek Zielinski is an experienced technology and financial journalist with a passion for cybersecurity and futurology.

Continue Reading


Fortune 500’s race for generative AI breakthroughs



Deanna Ritchie

As excitement around generative AI grows, Fortune 500 companies, including Goldman Sachs, are carefully examining the possible applications of this technology. A recent survey of U.S. executives indicated that 60% believe generative AI will substantially impact their businesses in the long term. However, they anticipate a one to two-year timeframe before implementing their initial solutions. This optimism stems from the potential of generative AI to revolutionize various aspects of businesses, from enhancing customer experiences to optimizing internal processes. In the short term, companies will likely focus on pilot projects and experimentation, gradually integrating generative AI into their operations as they witness its positive influence on efficiency and profitability.

Goldman Sachs’ Cautious Approach to Implementing Generative AI

In a recent interview, Goldman Sachs CIO Marco Argenti revealed that the firm has not yet implemented any generative AI use cases. Instead, the company focuses on experimentation and setting high standards before adopting the technology. Argenti recognized the desire for outcomes in areas like developer and operational efficiency but emphasized ensuring precision before putting experimental AI use cases into production.

According to Argenti, striking the right balance between driving innovation and maintaining accuracy is crucial for successfully integrating generative AI within the firm. Goldman Sachs intends to continue exploring this emerging technology’s potential benefits and applications while diligently assessing risks to ensure it meets the company’s stringent quality standards.

One possible application for Goldman Sachs is in software development, where the company has observed a 20-40% productivity increase during its trials. The goal is for 1,000 developers to utilize generative AI tools by year’s end. However, Argenti emphasized that a well-defined expectation of return on investment is necessary before fully integrating generative AI into production.

To achieve this, the company plans to implement a systematic and strategic approach to adopting generative AI, ensuring that it complements and enhances the skills of its developers. Additionally, Goldman Sachs intends to evaluate the long-term impact of generative AI on their software development processes and the overall quality of the applications being developed.

Goldman Sachs’ approach to AI implementation goes beyond merely executing models. The firm has created a platform encompassing technical, legal, and compliance assessments to filter out improper content and keep track of all interactions. This comprehensive system ensures seamless integration of artificial intelligence in operations while adhering to regulatory standards and maintaining client confidentiality. Moreover, the platform continuously improves and adapts its algorithms, allowing Goldman Sachs to stay at the forefront of technology and offer its clients the most efficient and secure services.

Featured Image Credit: Photo by Google DeepMind; Pexels; Thank you!

Deanna Ritchie

Managing Editor at ReadWrite

Deanna is the Managing Editor at ReadWrite. Previously she worked as the Editor in Chief for Startup Grind and has over 20+ years of experience in content management and content development.

Continue Reading


UK seizes web3 opportunity simplifying crypto regulations



Deanna Ritchie

As Web3 companies increasingly consider leaving the United States due to regulatory ambiguity, the United Kingdom must simplify its cryptocurrency regulations to attract these businesses. The conservative think tank Policy Exchange recently released a report detailing ten suggestions for improving Web3 regulation in the country. Among the recommendations are reducing liability for token holders in decentralized autonomous organizations (DAOs) and encouraging the Financial Conduct Authority (FCA) to adopt alternative Know Your Customer (KYC) methodologies, such as digital identities and blockchain analytics tools. These suggestions aim to position the UK as a hub for Web3 innovation and attract blockchain-based businesses looking for a more conducive regulatory environment.

Streamlining Cryptocurrency Regulations for Innovation

To make it easier for emerging Web3 companies to navigate existing legal frameworks and contribute to the UK’s digital economy growth, the government must streamline cryptocurrency regulations and adopt forward-looking approaches. By making the regulatory landscape clear and straightforward, the UK can create an environment that fosters innovation, growth, and competitiveness in the global fintech industry.

The Policy Exchange report also recommends not weakening self-hosted wallets or treating proof-of-stake (PoS) services as financial services. This approach aims to protect the fundamental principles of decentralization and user autonomy while strongly emphasizing security and regulatory compliance. By doing so, the UK can nurture an environment that encourages innovation and the continued growth of blockchain technology.

Despite recent strict measures by UK authorities, such as His Majesty’s Treasury and the FCA, toward the digital assets sector, the proposed changes in the Policy Exchange report strive to make the UK a more attractive location for Web3 enterprises. By adopting these suggestions, the UK can demonstrate its commitment to fostering innovation in the rapidly evolving blockchain and cryptocurrency industries while ensuring a robust and transparent regulatory environment.

The ongoing uncertainty surrounding cryptocurrency regulations in various countries has prompted Web3 companies to explore alternative jurisdictions with more precise legal frameworks. As the United States grapples with regulatory ambiguity, the United Kingdom can position itself as a hub for Web3 innovation by simplifying and streamlining its cryptocurrency regulations.

Featured Image Credit: Photo by Jonathan Borba; Pexels; Thank you!

Deanna Ritchie

Managing Editor at ReadWrite

Deanna is the Managing Editor at ReadWrite. Previously she worked as the Editor in Chief for Startup Grind and has over 20+ years of experience in content management and content development.

Continue Reading

Copyright © 2021 Seminole Press.