The risks and dangers of AI

Artificial Intelligence (AI) is ubiquitous in 2024, fundamentally transforming major sectors including healthcare, transportation, entertainment, and now cryptocurrency trading. Though there are monumental transformational possibilities with this disruptive power, there are also potential significant risks that lurk beneath the surface. We explore how AI impacts the crypto market and other economic sectors, what opportunities and dangers it brings, and how businesses and investors can mitigate these risks.

AI applications

AI currently works to enhance efficiency, accuracy, and productivity across various industries. For example, AI models calculate stock market trends, support disease diagnosis in healthcare, and improve general mobility in the transportation sector.

In cryptocurrency trading, AI provides traders with tools that offer entirely new possibilities for market analysis and decision-making. Despite these impressive advancements, the rapid integration of AI raises critical questions about potential risks and dangers. Let’s look at these in more detail. 

AI and cryptocurrencies

AI in crypto trading

AI technologies have been used in crypto trading for some time, providing advanced trading algorithms that analyse market trends and execute trades at high speeds. While AI-driven systems improve efficiency, they also introduce new risks.

How AI is used in crypto trading:

• Market analysis: AI models analyse large amounts of market data to identify trading opportunities.

• Automated trading: AI systems execute trades automatically based on predefined strategies and market conditions.

• Risk management: AI systems help traders minimise risks by monitoring market movements in real time and delivering predictive alerts.

The role of AI in token generation

In addition to optimising the trading process, AI plays an increasingly important role in creating new cryptocurrencies and developing token distribution strategies.

• Token optimisation: AI can be used to design optimal tokenomics models, ensuring that supply and demand for a token remain balanced.

• ICO marketing: Using AI, targeted marketing campaigns can be created to attract potential investors and positively shape a project’s perception.

• Token distribution: AI algorithms can also facilitate a fair distribution of tokens during ICOs or other sales mechanisms, helping to prevent manipulation.

AI in risk management for cryptocurrencies

A key advantage of AI in the cryptocurrency market lies in its ability to effectively manage risks and offer better protective measures to investors.

• Automated risk assessment: AI can create real-time risk assessments based on historical data and current market trends.

• Security monitoring: AI helps detect irregularities and potential security threats within the network early on.

• Fraud prevention: AI systems continuously monitor transactions to identify and flag fraudulent activities, such as unusual trading volumes.

AI and decentralised finance (DeFi) 

AI is transforming decentralised finance (DeFi) by creating new possibilities for automated financial products and services.

• AI-powered smart contracts: These contracts can be executed autonomously without a third party, with AI algorithms helping adjust conditions based on real-world data.

• Lending and credit scoring: AI can analyse the creditworthiness of users in DeFi networks to enable low-risk lending.

• Liquidity management: AI models assist in efficiently managing liquidity pools and determining optimal times for trades.

AI and DeFi work together to facilitate access to financial services. Despite these advantages, AI-driven trading systems can also be exploited for fraudulent activities.

Common AI-driven frauds

AI technologies can significantly ease fraud in crypto trading, deceiving investors and launching fraudulent crypto projects faster than before.

Examples of AI-driven fraud include:

• Pump-and-dump schemes: AI algorithms manipulate cryptocurrency prices by artificially inflating or deflating market values.

• Rug pulls: Fraudulent developers use AI to artificially hype a crypto project, allowing them to suddenly cash out all investments.

• Fake ICOs: AI-generated content promotes fraudulent Initial Coin Offerings (ICOs) to persuade investors to fund non-existent projects.

Protection against AI fraud requires vigilance and a strong awareness of common scams.

Protecting against AI fraud

Follow these tips to avoid falling victim to AI-driven scams in crypto trading.

• Thorough research: Examine each cryptocurrency investment thoroughly, including the project team and their track record.

• Verify sources: Ensure that information about crypto projects comes from reputable and verified sources.

• Remain sceptical: Be cautious of investment opportunities promising high returns with low risk, as these are often too good to be true.

AI and the Economy

Economic Impacts

AI is transforming not only the crypto market but also traditional business models and economies, requiring companies to innovate and disrupt established industries.

Examples of economic impacts include:

• Automation: AI-driven automation reduces labour costs but can also lead to job losses and wage pressures.

• Logistics and supply chains: AI optimises inventory, route planning, and supply chain management, putting pressure on traditional logistics companies to adapt quickly or risk losing market share.

• Banking: AI-powered chatbots revolutionise customer service while reducing the need for human advisors and employees.

Businesses must address these economic impacts by responsibly integrating AI and preparing for the associated changes.

Risk management

To minimise AI risks, companies must adhere to ethical guidelines and practices. AI systems should be designed to be transparent, fair, and responsible to mitigate potential harm.

How companies can reduce AI risks:

• Ethical AI practices: Special AI policies ensure that AI development and usage promote fairness, transparency, and accountability.

• AI audits: Regular audits of AI systems identify and correct biases and security vulnerabilities.

• Stakeholder involvement: Involving various stakeholders in AI decision-making processes helps consider diverse perspectives and concerns.

Implementing these measures allows companies to leverage the benefits of AI while managing associated risks.

General risks and dangers of AI

Job displacement

Another major issue related to AI is the displacement of jobs. Automation and AI-powered technologies are increasingly taking on tasks traditionally performed by humans.

Industries most affected by AI-related job displacement include:

• Manufacturing: Automation and robotics reduce the need for manual labour in factories.

• Retail: Automated checkout systems and inventory management decrease demand for cashiers and stock controllers.

• Transport: Self-driving vehicles threaten the jobs of drivers in logistics and delivery services.

• Creative professions: AI can take on tasks in graphic design, music production, and journalism previously handled by creative professionals.

Although AI also creates new jobs in research, technical processing, and data analysis, the transition is challenging for workers in traditional roles. Some responses to this shift may involve investing in retraining and education opportunities.

Bias and discrimination

AI systems are trained on large datasets that may contain biases from the real world. If not addressed, this discrimination is perpetuated or even amplified by AI.

For example, certain AI systems have shown biases that stigmatise women or people with darker skin tones based on outdated generalisations.

This has consequences in various areas of professional and social life:

• Job applications: Discriminatory AI algorithms can favour certain profiles, leading to unequal employment opportunities.

• Law enforcement: Biased predictive law enforcement systems may disproportionately target minorities.

• Healthcare: AI systems trained mainly on data from male patients may provide inappropriate recommendations and treatment suggestions.

This type of bias and discrimination in AI can be mitigated by improving the diversity of training datasets and conducting comprehensive fairness audits.

Security threats

AI technologies can be used by criminals for cyberattacks and hacking. Various AI tools are designed specifically to steal data or infiltrate IT systems. Examples of AI in cyberattacks include:

• Automated phishing: AI-generated phishing emails mimic legitimate communications that enable fraud.

• Deepfakes: AI-generated fake videos or audio recordings increasingly deceive individuals or organisations.

• Malware: AI can produce sophisticated malware that evolves autonomously, making it harder to detect.

Such attacks pose a serious threat to the security of companies and individuals. To protect against these dangers, ongoing investments in cybersecurity measures and the development of AI-based defence mechanisms are essential.

Conclusion

AI offers numerous opportunities but also presents significant challenges. Automation, enhanced analyses, and improved efficiency are clear advantages in cryptocurrency trading, but associated risks like market manipulation and fraud must be kept in check.

Moreover, the effects of AI extend beyond technical applications to economic and social spheres. Job displacement, algorithmic bias, and the threat of cyberattacks are serious risks that must be mitigated through continuous monitoring and improvements to AI systems.

With this in mind, it is vital to stay informed and keep your knowledge and understanding of the risks and dangers of AI up to date to harness the benefits of AI while minimising risks.

Frequently asked questions (FAQs) on AI risks

How does AI help in crypto trading?

AI analyses vast amounts of market data in real-time, detects patterns, and offers well-founded recommendations for buying and selling cryptocurrencies. Automated trading allows AI systems to execute trades faster, reducing human error and emotional decision-making.

What are the benefits of AI for risk management in the crypto market?

AI can assess risks effectively by combining historical data and current market trends to make forecasts. Additionally, AI continuously monitors the market and sends alerts when unusual or risky activities are detected.

How can AI assist with token generation and optimisation?

AI algorithms can design tokenomics that keep supply and demand balanced, stabilising a token's value. AI also facilitates fair token distribution during ICOs to prevent manipulation.

What is an AI-driven smart contract?

An AI-driven smart contract executes transactions autonomously, fulfilling terms and conditions based on real-world data. These intelligent contracts offer flexibility as AI can make real-time adjustments without human intervention.

What are the dangers of AI-driven fraud in the crypto sector?

AI can be used to manipulate the market, as seen in pump-and-dump schemes where prices are artificially inflated. Fraudsters also use AI to promote fake but realistic projects, such as rug pulls or fake ICOs.

How is AI used in DeFi?

In DeFi, AI helps automate credit decisions, quickly and accurately assessing users’ creditworthiness. AI also manages liquidity pools efficiently, enabling optimised handling of smart contracts based on data-driven decisions.

What are the biggest risks of using AI in the crypto market?

One major risk is that AI systems may make poor decisions due to faulty data or algorithms, causing significant losses. Lack of transparency in AI decision-making could also undermine investor trust and enable market manipulation.

How can AI contribute to fraud prevention in crypto trading?

AI continuously monitors market behaviour to identify suspicious transactions or patterns that may indicate fraudulent activity. AI systems can also report unusually high trading volumes or price changes in real time, triggering protective measures.

What regulatory measures exist to counter AI-related risks in crypto trading?

Regulations like the EU AI Act demand greater transparency in AI systems, especially regarding decision-making. These laws aim to ensure that AI operates fairly and ethically, aligning with data privacy and preventing market manipulation and abuse.

How can investors protect themselves from AI-driven scams in crypto trading?

Investors should conduct thorough research on crypto projects and their developers to minimise risks. It is also advisable to trade only on trusted and established platforms and to be sceptical of offers promising unrealistically high returns.