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Top Three Data Privacy Issues Facing AI Today

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AI (artificial intelligence) has caused frenzied excitement among consumers and businesses alike driven by a passionate belief that LLMs (large language models) and tools like ChatGPT will transform the way we study, work and live.

But just like in the internet’s early days, users are jumping in without considering how their personal data is used – and the impact this could have on their privacy.

There have already been countless examples of data breaches within the AI space. In March 2023, OpenAI temporarily took ChatGPT offline after a ‘significant’ error meant users were able to see the conversation histories of strangers.

That same bug meant the payment information of subscribers including names, email addresses and partial credit card numbers were also in the public domain.

In September 2023, a staggering 38 terabytes of Microsoft data was inadvertently leaked by an employee, with cybersecurity experts warning this could have allowed attackers to infiltrate AI models with malicious code.

Researchers have also been able to manipulate AI systems into disclosing confidential records.

In just a few hours, a group called Robust Intelligence was able to solicit personally identifiable information from Nvidia software and bypass safeguards designed to prevent the system from discussing certain topics.

Lessons were learned in all of these scenarios, but each breach powerfully illustrates the challenges that need to be overcome for AI to become a reliable and trusted force in our lives.

Gemini, Google’s chatbot, even admits that all conversations are processed by human reviewers underlining the lack of transparency in its system.

“Don’t enter anything that you wouldn’t want to be reviewed or used,” says an alert to users warns.

AI is rapidly moving beyond a tool that students use for their homework or tourists rely on for recommendations during a trip to Rome.

It’s increasingly being depended on for sensitive discussions and fed everything from medical questions to our work schedules.

Because of this, it’s important to take a step back and reflect on the top three data privacy issues facing AI today, and why they matter to all of us.

1. Prompts aren’t private

Tools like ChatGPT memorize past conversations in order to refer back to them later. While this can improve the user experience and help train LLMs, it comes with risk.

If a system is successfully hacked, there’s a real danger of prompts being exposed in a public forum.

Potentially embarrassing details from a user’s history could be leaked, as well as commercially sensitive information when AI is being deployed for work purposes.

As we’ve seen from Google, all submissions can also end up being scrutinized by its development team.

Samsung took action on this in May 2023 when it banned employees from using generative AI tools altogether. That came after an employee uploaded confidential source code to ChatGPT.

The tech giant was concerned that this information would be difficult to retrieve and delete, meaning IP (intellectual property) could end up being distributed to the public at large.

Apple, Verizon and JPMorgan have taken similar action, with reports suggesting Amazon launched a crackdown after responses from ChatGPT bore similarities to its own internal data.

As you can see, the concerns extend beyond what would happen if there’s a data breach but to the prospect that information entered into AI systems could be repurposed and distributed to a wider audience.

Companies like OpenAI are already facing multiple lawsuits amid allegations that their chatbots were trained using copyrighted material.

2. Custom AI models trained by organizations aren’t private

This brings us neatly to our next point while individuals and corporations can establish their custom LLM models based on their own data sources, they won’t be fully private if they exist within the confines of a platform like ChatGPT.

There’s ultimately no way of knowing whether inputs are being used to train these massive systems or whether personal information could end up being used in future models.

Like a jigsaw, data points from multiple sources can be brought together to form a comprehensive and worryingly detailed insight into someone’s identity and background.

Major platforms may also fail to offer detailed explanations of how this data is stored and processed, with an inability to opt out of features that a user is uncomfortable with.

Beyond responding to a user’s prompts, AI systems increasingly have the ability to read between the lines and deduce everything from a person’s location to their personality.

In the event of a data breach, dire consequences are possible. Incredibly sophisticated phishing attacks could be orchestrated and users targeted with information they had confidentially fed into an AI system.

Other potential scenarios include this data being used to assume someone’s identity, whether that’s through applications to open bank accounts or deepfake videos.

Consumers need to remain vigilant even if they don’t use AI themselves. AI is increasingly being used to power surveillance systems and enhance facial recognition technology in public places.

If such infrastructure isn’t established in a truly private environment, the civil liberties and privacy of countless citizens could be infringed without their knowledge.

3. Private data is used to train AI systems

There are concerns that major AI systems have gleaned their intelligence by poring over countless web pages.

Estimates suggest 300 billion words were used to train ChatGPT that’s 570 gigabytes of data with books and Wikipedia entries among the datasets.

Algorithms have also been known to depend on social media pages and online comments.

With some of these sources, you could argue that the owners of this information would have had a reasonable expectation of privacy.

But here’s the thing many of the tools and apps we interact with every day are already heavily influenced by AI and react to our behaviors.

The Face ID on your iPhone uses AI to track subtle changes in your appearance.

TikTok and Facebook’s AI-powered algorithms make content recommendations based on the clips and posts you’ve viewed in the past.

Voice assistants like Alexa and Siri depend heavily on machine learning, too.

A dizzying constellation of AI startups is out there, and each has a specific purpose. However, some are more transparent than others about how user data is gathered, stored and applied.

This is especially important as AI makes an impact in the field of healthcare from medical imaging and diagnoses to record-keeping and pharmaceuticals.

Lessons need to be learned from the internet businesses caught up in privacy scandals over recent years.

Flo, a women’s health app, was accused by regulators of sharing intimate details about its users to the likes of Facebook and Google in the 2010s.

Where do we go from here

AI is going to have an indelible impact on all of our lives in the years to come. LLMs are getting better with every passing day, and new use cases continue to emerge.

However, there’s a real risk that regulators will struggle to keep up as the industry moves at breakneck speed.

And that means consumers need to start securing their own data and monitoring how it is used.

Decentralization can play a vital role here and prevent large volumes of data from falling into the hands of major platforms.

DePINs (decentralized physical infrastructure networks) have the potential to ensure everyday users experience the full benefits of AI without their privacy being compromised.

Not only can encrypted prompts deliver far more personalized outcomes, but privacy-preserving LLMs would ensure users have full control of their data at all times and protection against it being misused.


Chris Were is a CEO of Verida, a decentralized, self-sovereign data network empowering individuals to control their digital identity and personal data. Chris is an Australian-based technology entrepreneur who has spent more than 20 years devoted to developing innovative software solutions.

 

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Disclaimer: Opinions expressed at The Daily Hodl are not investment advice. Investors should do their due diligence before making any high-risk investments in Bitcoin, cryptocurrency or digital assets. Please be advised that your transfers and trades are at your own risk, and any loses you may incur are your responsibility. The Daily Hodl does not recommend the buying or selling of any cryptocurrencies or digital assets, nor is The Daily Hodl an investment advisor. Please note that The Daily Hodl participates in affiliate marketing.

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Why the US Should Reevaluate Its Approach to the Bitcoin Mining Industry

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Bitcoin mining has garnered a reputation for being wasteful and dirty though this couldn’t be further from the truth.

Bitcoin mining can be as ‘green’ as any industry and is an essential aspect of Bitcoin overall.

After Bitcoin mining was banned in countries such as China and others, it caught on in a big way in the US, quickly becoming a major industry with a notable presence in towns across the US.

Cryptocurrency mining the vast majority of which is Bitcoin mining requires between 0.6% and 2.3% of all electricity used in the US.

And globally it requires between 0.2% and 0.9% of all power as much as Greece and Australia.

The carbon footprint of mining in the US is 78.7 million metric tons of CO2 per year. The industry is growing so fast that regulators are moving to understand it better.

The US EIA (Energy Information Administration) moved to require cryptocurrency mining businesses to share power usage details and has considered fines against miners.

The EIA has faced legal obstacles in the wake of a miner-led lawsuit.

Regulators must understand crypto mining can be green

The federal government has made it clear that robust and enforceable regulation is likely coming to the US Bitcoin mining industry, and therefore the community must work together toward reasonable legislation.

The bottom line is simple Bitcoin mining could one day be a net positive for the environment.

Bitcoin’s proof-of-work process has grown increasingly more energy-efficient as more miners look towards renewable energy sources such as wind, solar and hydropower  not coal or natural gas.

The Bitcoin Mining Council, a bitcoin industry group, has shown that 60% of mining is done with renewables.

Nonetheless, the US EIA requires cryptocurrency miners to share their power usage details to regulate high power usage. There are only a few ways for miners to respond.

The best way is to make efforts to create zero-carbon emitting mines, while also agreeing to curtail mining activities during emergencies, which would then allow them to potentially function as a buffer of sorts for the grid.

According to Joshua Rhodes, an energy research associate with the University of Texas at Austin, flexible energy loads are good for the grid.

If crypto miners curtail their energy use during peak times, their annual load can be slashed by 13-15%, and could thereby reduce carbon emissions, improve grid resiliency in high-stress periods and foster a shift to renewables.

The importance of Bitcoin mining

Bitcoin fosters financial inclusion and empowers the unbanked.

Bitcoin is an alternative pathway to the financial system, allowing individuals to engage in transactions, savings and even access loans without the need for a bank account or credit history.

Without mining, Bitcoin would be neither secure nor deflationary.

Beyond merely validating transactions and securing the network, Bitcoin miners are increasingly becoming integral components of a broader digital infrastructure.

Their extensive computational resources offer potential for innovative services such as decentralized cloud computing and enhanced cybersecurity measures.

Furthermore, as renewable energy becomes more prevalent in mining operations, these entities could play a pivotal role in promoting sustainable practices within the digital economy.

The increased use of renewable energy not only helps reduce the environmental impact of mining operations but also improves profitability by lowering energy costs in the long run.

Collaborations between miners and renewable energy providers can stimulate economic development in regions with abundant clean energy resources.

As a mobile and flexible demand for electricity, Bitcoin mining operations can stabilize grids by using excess renewable energy that would otherwise go to waste due to storage limits.

Consequently, this unique symbiosis between Bitcoin mining practices and renewable energy advancements fosters a mutually beneficial relationship, promoting sustainability while driving forward technological innovation in both sectors.

The US must embrace crypto mining and regulate it in a sensible manner, which can be done at the policy level.

New industries, much dirtier than crypto, have been regulated by municipalities, states and the federal government while not killing said industry.

The same must be done for Bitcoin and crypto mining, and the Bitcoin community must speak up to make this so.


Kadan Stadelmann is a blockchain developer, operations security expert and Komodo Platform‘s chief technology officer. His experience ranges from working in operations security in the government sector and launching technology startups to application development and cryptography. Kadan started his journey into blockchain technology in 2011 and joined the Komodo team in 2016.

 

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Disclaimer: Opinions expressed at The Daily Hodl are not investment advice. Investors should do their due diligence before making any high-risk investments in Bitcoin, cryptocurrency or digital assets. Please be advised that your transfers and trades are at your own risk, and any loses you may incur are your responsibility. The Daily Hodl does not recommend the buying or selling of any cryptocurrencies or digital assets, nor is The Daily Hodl an investment advisor. Please note that The Daily Hodl participates in affiliate marketing.

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Trade Finance – Embracing Innovation for a Secure Future

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Global trade relies heavily on trade finance a complex system that facilitates international transactions between businesses.

While it fuels economic growth, trade finance also presents inherent risks that financial institutions and regulators must address.

This guide delves into these risks and equips you with practical strategies to effectively manage them.

Understanding trade finance risks

Several factors contribute to the risk landscape in trade finance.

High transaction volume and complexity

The problem

The sheer number and intricate details involved in trade transactions make it difficult to identify suspicious activity.

Manual processes further complicate matters, increasing the chance of errors and fraudulent documents going unnoticed.

Actionable step

Implement automated transaction monitoring systems with anomaly detection capabilities.

These systems can analyze vast amounts of data to identify unusual patterns that might indicate fraud, money laundering or other suspicious activity.

Time constraints and competition

The problem

Tight deadlines and fierce competition in the trade finance market can pressure institutions to rush the due diligence process, compromising its effectiveness.

This haste can lead to overlooking red flags and approving risky transactions.

Actionable step

Establish clear timeframes for trade finance transactions. Prioritize thorough due diligence over speed.

A well-defined process ensures all necessary checks are completed before approving a transaction, mitigating potential risks.

Lack of standardized controls

The problem

Inconsistent regulations across different countries create loopholes that criminals can exploit for money laundering and other financial crimes.

The lack of standardization makes it difficult for institutions to track and monitor suspicious activity effectively.

Actionable step

Advocate for international cooperation and information sharing among regulatory bodies.

Standardized regulations and a global information sharing framework can create a more robust system for identifying and preventing financial crimes in trade finance.

Dual-use goods

The problem

Trade involving dual-use goods items with both civilian and military applications adds complexity and increases the risk of illegal activities.

The ambiguous nature of these goods makes it challenging to determine their true end-use.

Actionable step

Implement robust due diligence for dual-use goods trade.

This includes conducting enhanced risk assessments, verifying licenses thoroughly and ensuring compliance with export control regulations.

Building a strong due diligence framework

To effectively navigate these risks, financial institutions need a robust due diligence framework.

Comprehensive risk assessments

Go beyond the basics

Regularly assess potential threats posed by various factors. This includes the following.

  • Customer profiles Analyze customer background, business activities, past transactions and reputation. Identify high-risk customers based on industry, location or ownership structure.
  • Transaction types Evaluate the inherent risk associated with different trade finance products (e.g., letters of credit, documentary collections). Complex transactions or those involving large sums of money warrant additional scrutiny.
  • Geographic locations – Research the political and economic stability of countries involved in the transaction. Countries with high corruption or weak regulatory environments pose greater risks.

Develop a risk-based approach

Assign risk ratings to different scenarios based on your assessments. This allows you to tailor due diligence procedures to the specific level of risk associated with each transaction.

Stringent verification processes

KYC (know your customer)

Implement a robust KYC program to verify the identities and legitimacy of all parties involved in a trade transaction. This includes the following.

  • Customer identification Collect and verify official documents to confirm the identities of individuals and businesses involved.
  • Beneficiary ownership identification Identify the UBOs (ultimate beneficial owners) of companies involved. This helps uncover potential shell companies or hidden agendas.
  • CDD (customer due diligence) Gather information on the customer’s business activities, financial situation and reputation.

EDD (enhanced due diligence)

For high-risk transactions or customers, conduct deeper due diligence investigations. This might involve the following.

  • Source of funds verification Investigate the origin of funds being used in the transaction to combat money laundering risks.
  • Third-party verification Verify information provided by the customer with independent sources.

Sanctions screening

  • Stay up-to-date Utilize automated sanctions screening tools that are regularly updated with the latest sanctions lists from international bodies (e.g., OFAC, UN Security Council).
  • Screen all parties Screen all parties involved in the transaction against sanctions lists, including customers, beneficiaries and intermediaries.
  • Red flag alerts Configure screening tools to generate alerts for potential matches, requiring further investigation before proceeding with the transaction.

Strong audit trails

  • Maintain detailed records For every trade finance transaction, maintain a comprehensive audit trail that includes all relevant documents, communication records and risk assessments.
  • Tamper-proof systems Store audit trails in secure, tamper-proof electronic systems to ensure data integrity and facilitate retrievability for future reference or regulatory investigations.
  • Regular reviews Conduct periodic reviews of audit trails to identify any patterns or inconsistencies that might indicate potential issues.

Embracing innovation for a secure future

The risk landscape is constantly evolving, demanding innovative solutions.

Digitization

One way to combat these risks is through digitization. This means using automation and digital tools to streamline processes.

This not only reduces errors caused by humans but also speeds up transactions and makes everything more efficient overall.

Examples of digitization in trade finance include using electronic documents instead of paper and automating data exchange between different parties.

Blockchain technology

Blockchain uses a special digital record-keeping system that can’t be tampered with. This makes it much more secure and transparent than traditional methods.

Blockchain has the potential to completely change trade finance by streamlining processes, reducing the risk of fraud and increasing trust among everyone involved.

Information sharing

Fostering a culture of information sharing among financial institutions, regulatory bodies and law enforcement allows for quicker identification and response to emerging threats.

This can involve creating secure platforms for information exchange and collaborating on investigations.

Combating TBML (trade-based money laundering)

TBML requires specialized strategies.

Transaction monitoring and document review

Implement automated transaction monitoring systems and conduct meticulous document reviews to identify suspicious activities and red flags associated with TBML.

This helps identify suspicious activity and red flags that might indicate TBML attempts. Examples of red flags include the following.

  • Significant price discrepancies between invoiced value and fair market value of goods.
  • Unnecessary complexity in trade transactions, such as unnecessary intermediaries or unusual routing of goods.
  • Involvement of companies or individuals located in high-risk jurisdictions known for weak regulations or money laundering activity.

Red flag identification

Develop and maintain a comprehensive list of red flags to detect potential TBML attempts. Train staff to recognize these red flags and report them promptly.

Stringent import/export licensing

Collaborate with government agencies to improve import/export licensing procedures.

This can involve stricter controls and information sharing to make it more difficult for criminals to exploit loopholes and utilize trade for illicit purposes.

Document verification

Implement rigorous document verification processes to detect and prevent the use of duplicate or fraudulent documents in trade finance transactions.

This may involve collaborating with trusted third-party verification providers.

Conclusion

Trade finance plays a vital role in global trade, but it also carries inherent risks.

Financial institutions can navigate these challenges and create a secure and efficient trade finance landscape by adopting a multi-pronged approach.

The key to success lies in continuous monitoring. Institutions must constantly adapt their risk management frameworks to stay ahead of evolving threats.

Additionally, information sharing plays a vital role in upholding the principles of financial integrity.

By openly communicating suspicious activity and collaborating on investigations, institutions can create a more secure trade finance environment for everyone involved.


Shahzaib Muhammad Feroz, a distinguished member of the financial intelligence unit at AKS iQ, serves as a linchpin in fortifying the integrity of AML (anti-money laundering) efforts. Drawing upon his extensive expertise in forensic accounting and regulatory compliance, Shahzaib is instrumental in uncovering illicit financial activities and mitigating associated risks.

 

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Disclaimer: Opinions expressed at The Daily Hodl are not investment advice. Investors should do their due diligence before making any high-risk investments in Bitcoin, cryptocurrency or digital assets. Please be advised that your transfers and trades are at your own risk, and any loses you may incur are your responsibility. The Daily Hodl does not recommend the buying or selling of any cryptocurrencies or digital assets, nor is The Daily Hodl an investment advisor. Please note that The Daily Hodl participates in affiliate marketing.

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Bitcoin Halving 2024 – Insights From Historical Performance

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Bitcoin halving 2024 perhaps the most eagerly awaited event in the crypto world this year is now less than a month away.

While the abundance of countdown timers scattered across various platforms highlights its significance, its true implications for the crypto market remain somewhat ambiguous.

Officially, the Bitcoin halving signifies a halving of Bitcoin’s mining reward. However, its impact extends beyond mining dynamics alone.

Occurring roughly every four years, these events have historically served as pivotal moments in Bitcoin’s journey, shaping its price trajectory and influencing market sentiment.

As we approach the fourth Bitcoin halving event scheduled for a block height of 740,000 examining the current state of the crypto market in light of past performance provides valuable insights into interpreting market dynamics.

Let’s delve into the performance of the three previous Bitcoin halving events.

Bitcoin halving 2012

November 28, 2012, marked a historic moment in Bitcoin’s journey with its first halving event. As the block reward dwindled from 50 BTC to 25 BTC, Bitcoin underwent a significant transformation.

What ensued was truly extraordinary. Bitcoin’s price surged from a humble $11 to an astonishing $1,110 by December 2013, showcasing its revolutionary potential as a digital asset.

This meteoric rise not only captured the attention of investors but also propelled Bitcoin into the mainstream spotlight, laying the groundwork for its ascent to prominence in the financial realm.

Bitcoin halving 2016

Fast forward to July 9, 2016, and Bitcoin encountered its second halving event.

With the block reward slashed once again this time from 25 BTC to 12.5 BTC Bitcoin embarked on another remarkable journey.

Soaring from approximately $650 prior to the halving, its price skyrocketed to an astounding $19,500 by December 2017, marking a 30-fold increase in just six months.

While Bitcoin basked in the limelight, the cryptocurrency landscape witnessed the emergence of altcoins and the proliferation of initial coin offergins (ICOs), indicating a surge in interest and investment in blockchain technology.

Bitcoin halving 2020

Amid the global upheaval caused by the COVID-19 pandemic, Bitcoin’s third halving event unfolded on May 11, 2020. Despite the economic uncertainty, Bitcoin adhered to a familiar pattern.

Its price surged eight-fold in less than a year, climbing from around $8,900 before halving to over $64,000 by April 2021.

This period also witnessed significant institutional endorsement, with notable investors like Paul Tudor Jones and Michael Saylor publicly backing Bitcoin, further solidifying its status as a reliable store of value.

Looking to the future Bitcoin halving 2024

As we stand on the brink of the fourth Bitcoin halving event, the stage is set for another captivating chapter in the Bitcoin saga.

With the block reward poised to drop to 3,125 new BTC, the cryptocurrency world eagerly anticipates what lies ahead.

Drawing insights from past halvings, we can forecast certain trends.

Pre-halving rally

Historically, Bitcoin has witnessed significant price rallies preceding halving events, fueled by investors’ anticipation of reduced supply and potential price appreciation.

Post-halving correction and consolidation

Following the halving, Bitcoin typically undergoes a period of correction and consolidation as the market adjusts to the altered supply dynamics.

This phase often manifests heightened volatility as market participants navigate the new landscape.

Next bull run

After the initial adjustment period, Bitcoin tends to embark on a major bull run, propelling prices to new highs.

This phase commonly reaches its zenith approximately 18 months after the halving event, as Bitcoin gains momentum and attracts renewed interest from investors.

Institutional interest

With each halving cycle, we’ve observed a surge in institutional interest in Bitcoin.

Institutional investors recognizing the potential of digital assets play a pivotal role in driving sustained price appreciation as they seek exposure to this burgeoning asset class.

In conclusion, while past performance is not indicative of future results, historical data shows that Bitcoin halving events are catalysts for significant price movements and increased market activity.

As we approach Bitcoin halving 2024, investors and enthusiasts will be closely monitoring developments and awaiting the next chapter in Bitcoin’s evolution.


Esin Syonmez is a content writer at Morpher, a company which strives to make trading accessible to all, where she contributes to the company’s mission of financial inclusion and democratizing trading worldwide.

 

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Disclaimer: Opinions expressed at The Daily Hodl are not investment advice. Investors should do their due diligence before making any high-risk investments in Bitcoin, cryptocurrency or digital assets. Please be advised that your transfers and trades are at your own risk, and any loses you may incur are your responsibility. The Daily Hodl does not recommend the buying or selling of any cryptocurrencies or digital assets, nor is The Daily Hodl an investment advisor. Please note that The Daily Hodl participates in affiliate marketing.

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