While AI is increasingly becoming a common practice in organisations, the ability of organisations to develop better growth prospects and more efficient strategies and customised consumer experiences also emerges clearly. AI brings unseen possibilities, such as automating decisions and delivering distinctively targeted advertising campaigns.

However, this technological advancement has not come easy without a set of problems. For instance, AI has alarmed privacy issues, the main reason being that systems demand personal data as inputs, and this acts as a violation of customer trust between firms and customers. Apart from that, the possibility of involuntary biases in the algorithms themselves, whereby an AI system unwittingly designs bias into the algorithm, resulting in “unfair” results, could go a long way in straining brand image and consumer trust.

Regardless, there is no doubt that AI has profoundly transformed the rapidly growing marketing technology (martech) industry, especially in the face of these aforementioned ethical issues. While AI optimises automation, increases customer satisfaction and improves analytical capabilities, organisations have to find the right balance between innovation and accountability. In this article, we will explore what these issues are and how they can be effectively addressed.

Essential ethical considerations to address

As AI continues to penetrate different industries, it has never been more urgent to raise awareness and ensure that AI is properly implemented. According to Forbes, more than 51 per cent of company leaders believe that AI transparency and ethics are critical to their operations, and 41 per cent of top executives have halted the deployment of AI technologies due to a potential ethical concern.

Transparency in the context of AI means that the functioning of artificial intelligence should be perceptible and understandable, while the process of making decisions should conform to ethical norms and general human values. One can find an example of transparency in the case of many companies employing AI to understand the behaviour of customers, targeting their advertisements and the overall marketing management.

To support the increase in transparency, some organisations have started giving customers more information about the usage of their data. AI transparency is also important where the risks are especially high that the consequences of AI decisions will impact lives or have large social outcomes, such as in healthcare and finance.

Another ethical consideration that has to be discussed is the issue of bias and discrimination in AI. AI comes with many advantages but is not without its controversies, particularly on issues of bias and discrimination. This is due to the fact that most AI models are trained from large datasets that could mirror some of the bias in the society hence the biased results.

Also Read: Blockchain and AI copyright: A revolution in digital rights management

Bias in AI can stem from various sources such as: 

• Bias in training data: If the training data contains inherent biases, the AI system will likely reproduce these biases in its decision-making processes. For instance, in a study, scientists tasked AI with developing a facial recognition system designed to classify individuals into three categories based on their characteristics: doctors, criminals, and homemakers. However, the AI demonstrated bias in its decision-making, frequently labelling women as homemakers, Black men as criminals, and Latino men as janitors, and selecting women of all ethnicities less often as doctors.
• Algorithmic bias: Beyond the data, poorly designed algorithms can amplify existing biases or create new ones. In 2018, Amazon’s AI recruitment algorithm was designed to assess candidates based on their fit for different roles. However, due to the underrepresentation of women in technical positions, the system developed a bias, favouring male applicants as it learned that men were historically preferred for these roles.
• Cognitive bias: Personal experiences and perspectives may lead developers to prioritise certain data over others, potentially skewing the AI’s outputs. For example, favouring data from a particular demographic or geographic region might result in an AI system that does not accurately reflect a global or diverse population. 

Strategies for mitigating bias and promoting fairness in AI

In 2024, Malaysia presented a PDP Bill that outlines significant changes in the Personal Data Protection Act (PDPA), including the definition of the terms, added responsibilities for data controllers, and increasing fines for non-compliance. The government regards these changes as great progress in enhancing data protection in the country and as a part of the continuous shift toward stricter privacy rules. This presents a good chance for companies to enhance their protection of data and bring them to par with global standards.

To start, there are various measures that companies can take to make the process ethical and responsible. One of the key strategies is to prioritise transparency, where businesses must provide clear insights into how AI algorithms operate. For instance, developing an explainable AI (XAI) plays a vital role in this process, as it offers techniques to help users understand and trust the decisions made by AI. By incorporating simplified visuals or user-friendly software interfaces, employees can grasp the underlying processes without relying on AI systems blindly. 

In addition to transparency, maintaining robust data security is critical. Research shows that 44 per cent of security decision-makers say their companies incorporate security and privacy measures from the outset when developing services, products, or applications.

Moreover, 87 per cent of consumers state that they won’t engage in business with a company if they have concerns about its security practices. This underscores the importance of continuous data monitoring, with dedicated personnel responsible for safeguarding information and preventing leaks. 

Also Read: How AI and automation can shape the future of farms

Companies should also ensure that their AI solutions comply with industry regulations and legal standards, as organisations that prioritise ethical AI are more likely to gain consumer confidence and create reliable AI systems. Furthermore, creating the role of human supervision as an AI control factor–where the AI makes suggestions that are then passed on to human experts to make the final decision is another positive since it assures that the systems are running fairly and effectively.

Implementing all these measures is critical in developing AI systems that are not only ethical but also efficient. At OpenMinds, we believe that we have a responsibility to lead by example, and we understand the importance of integrating ethical considerations into any AI development process.

Conclusion

In conclusion, reducing bias and encouraging fairness in the AI system is not only a technical issue but also an ethical issue. The strategies outlined are essential steps towards building trustworthy and ethical AI systems. We believe that these ethical considerations are especially important. As we continue to innovate in the martech industry, we aim to contribute to a future where AI benefits everyone, regardless of their background and identity.

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This article was first published on August 19, 2024.

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Asia’s 450 million smallholder farmers produce 80 per cent of the food consumed in the region and face increasing pressure to deliver sufficient, nutritious foods to a predicted regional population of five billion by 2050..

But climate-induced erratic weather patterns are threatening their ability to keep up with the demand. In India, the groundwater supply that is essential for agriculture has been steadily declining for years.

Coupled with erratic monsoon seasons and droughts, hundreds of millions of people’s livelihoods and food security are under. Southeast Asian farmers are also particularly vulnerable to changing rainfall patterns and warming temperatures due to the region’s location in the tropics.

Using a combination of crop protection products and digital tools such as artificial intelligence (AI), we can empower farmers to overcome the challenges of climate change and contribute to global food security.

Why technology matters in tackling climate change

Since the Green Revolution of the 1960s, developments in plant science have led to crop protection products that allowed farmers to improve the resilience of their crops against pests, diseases and continue growing amidst difficult conditions such as drought or flooding caused by climate change. Compared with 1960, the world now produces 150 per cent of more food on only 13 per cent more land.

Without crop protection products, 40 per cent of global rice and maize harvests would be lost every year and losses for fruits and vegetables could be as high as 50-90 per cent.

Also Read: COVID-19, the environment, and the tech ecosystem: what opportunity is available out there for us?

In addition, the agriculture industry is increasingly developing AI to help farmers yield healthier crops, control pests, monitor soil and growing conditions, organise data for farmers, help with workload, and improve a wide range of agriculture-related tasks in the entire food supply chain.

Climate change is an ever-growing threat that is leading to severe floods, harsh droughts and heatwaves, violent storms. For farming to be truly sustainable, we need regenerative agricultural practices that prioritises the enhancement of soil health and proper management of water and fertiliser usage.

Also Read: E Green Global bags US$9.2M from Korean social impact VC fund to expand its agritech facility

Continued investments into AI and plant science can accelerate the development of new and better crop protection products that meets our farmers’ needs for sustainable solutions.

While the public sector has traditionally been the driving force behind agricultural R&D, the growth has been slowed recently in many countries due to fiscally constrained policies. The private sector has increasingly filled these gaps.

Today, private investment into agricultural innovation has led to new technologies and production techniques that significantly boost productivity.

How to support agritech developments

The acceleration of breakthrough agri-tech solutions is one of the key cornerstones of Syngenta’s sustainability objectives– the Good Growth Plan, which aims to help farmers adapt to and mitigate the impact of climate change through our investment of US$2 billion that will drive the development of agri-tech and improve our crop protection products.

As part of this investment, Syngenta Crop Protection acquired Valagro, a global biologicals firm, in 2020. They are the leaders in providing innovative and effective solutions for plant nutrition, and care and their solutions complemented our range of bio stimulants and bio controls. Together, we are working towards meeting our goal of developing effective yet environmentally conscious products.

We also recently announced a collaboration with Hong Kong-based Insilico Medicine, an AI and deep learning company to accelerate the invention and development of new, more effective crop protection solutions that protect crops from diseases, weeds, and pests protecting ecosystems.

By bringing new solutions to APAC farmers faster and more efficiently through innovation, Syngenta can help them meet the ongoing challenges they face to enhance productivity and meet the demand for affordable, quality food.

Also Read: 7 Asian startups putting the spotlight on agriculture

The COVID-19 crisis has further intensified the challenges in agriculture, and technology will be a more important solution than ever before.

Beyond developments in crop protection products, I believe we’ll continue seeing a focus on technology to enhance precision agriculture, data-driven farming and the development of tools that will meet consumers’ demand for higher-quality foods grown with lesser residue products.

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This article was first published on March 15, 2021

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AI adoption is growing, with 85 per cent of financial institutions integrating AI tools to enhance speed, efficiency, and data analysis. However, these systems are no longer exclusive to large institutions or seasoned traders. By making investing safer and more approachable, AI is helping to democratise access to wealth-building opportunities for a broader audience across various levels of expertise.

Understanding the barriers and risks in trading

Trading in financial markets presents significant challenges due to market volatility and the necessity for rapid decision-making. For example, high-frequency trading (HFT), which involves executing a large number of orders at extremely high speeds, accounts for approximately 50 per cent of trading volume in the US stock market. This high-speed environment requires traders to process vast amounts of information in real-time, making it difficult for inexperienced individuals to compete effectively.

The rapid nature of HFT can lead to emotionally charged decision-making, increasing the risk of massive financial losses. This underscores the importance of maintaining emotional discipline and having access to real-time data and advanced trading tools to navigate the complexities of high-frequency trading successfully.

How AI is changing the landscape of trading

Unlike human traders, AI systems process vast amounts of data in real-time. This allows tech-driven solutions to react instantly to market fluctuations, which is a critical advantage in HFT. The ability to provide predictive analysis and trading signals with high accuracy helps investors make informed decisions while avoiding impulsive, emotion-driven choices. Larry Fink, CEO of BlackRock, has highlighted AI’s potential to boost productivity and transform margins across sectors, stating, “I believe that AI has a huge potential to increase productivity, increase knowledge base and transform margins across sectors.”

The predictive capabilities of AI are evident in platforms like StockSmart, which offers AI-powered trading signals with an accuracy rate exceeding 90 per cent, empowering traders to capitalise on emerging market opportunities. Moreover, AI continuously learns and adapts from data, identifying patterns and trading opportunities that human eyes might miss.

AI-driven platforms transforming investment and trading

StashAway

StashAway, a Singapore-based fintech startup, offers AI-driven portfolio management tailored to individual risk profiles and financial goals. The platform dynamically adjusts asset allocations in response to market conditions, which ensures optimal performance. StashAway’s user-friendly interface provides pre-built portfolios and comprehensive risk assessments, making it accessible to both novice and experienced investors. StashAway most recently raised US$25 million in a Series D funding round led by Sequoia Capital India, bringing total funding to around US$75.3 million.

Endowus

Also Singapore-based, Endowus offers an AI-powered investment platform that provides personalised portfolio management services. Utilising advanced algorithms, Endowus tailors investment strategies to individual risk profiles and financial goals, ensuring optimal asset allocation and automatic rebalancing. The platform’s user-friendly interface and comprehensive risk assessments make it accessible to both novice and experienced users. In August 2023, Endowus secured US$35 million in a funding round backed by Prosus Ventures and EDBI, bringing its total funding to US$95 million.

Also Read: The future is here: Seizing the first-mover advantage in AI entrepreneurship

Metafide

Designed for retail and institutional investors, Metafide integrates AI-driven predictive models with the insights of professional traders from around the world. Metafide employs recurrent neural networks (RNNs) and convolutional neural networks (CNNs) to analyse real-time data and predict price movements. Metafide also includes gamified features that allow traders to contribute real-time inputs on predicting short-term market movements, resulting in a platform that combines AI’s precision with human market understanding. Over 500,000 games have been played by more than 100,000 players on FIDE AI and RANGE FIDE(R) games powered by Mantle network.

The company has secured early-stage venture capital funding from investors such as Blockchain Founders Fund, Comma3 Ventures, and Cogitent. Co-Founder and CEO Frank Speiser, who previously co-founded SocialFlow, brings his expertise in combining AI and professional trading sentiment to Metafide. Speiser highlights the company’s unique approach: “Metafide focuses on incentivising community-driven insights, user-friendly experience, and trust through transparency.

The other critically important differentiator is that we own the entire value chain—we don’t send off market suggestions, but rather we execute the trades on behalf of our hedge fund partners. From the audience through to the completed trade, we have the ability and responsibility to modify or improve any part of the system.”

AI’s impact on the future of investing and trading

AI has the potential to make trading accessible to a broader range of individuals, including those who may not have a strong financial background. Hybrid models offer a new approach to risk management by allowing systems to adapt to both market conditions and investor behaviour. AI-driven platforms also provide educational resources that help users learn about market dynamics in a low-risk environment, an invaluable feature for beginners looking to avoid costly early mistakes.

As AI technology advances, it is poised to reshape the investment landscape further. With tools that offer risk assessments, real-time predictions, and educational support, AI allows investing to those who might otherwise be excluded, democratising access to financial growth and empowerment.

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The intersection of blockchain technology and artificial intelligence (AI) is an emerging frontier that holds great promise for addressing one of the most pressing issues in the digital age: copyright enforcement. With the proliferation of AI-generated content, the need for robust mechanisms to protect intellectual property rights has never been more critical.

This article explores how blockchain technology can provide innovative solutions to AI copyright challenges, offering a personal perspective on its potential supported by statistics and research.

The rise of AI-generated content

Artificial Intelligence has revolutionised content creation, bringing forth a new era where machines can produce music, art, literature, and more. AI algorithms, such as OpenAI’s GPT series, have demonstrated the ability to generate human-like text, while programs like DeepArt and DALL-E create visual art that rivals human artists. According to a report by MarketsandMarkets, the AI market size is expected to grow from US$150.2 billion in 2023 to US$1345.2 billion in 2030, reflecting the rapid adoption of AI technologies across various industries.

However, this surge in AI-generated content has raised significant questions about copyright ownership and enforcement. Traditional copyright laws, designed for human creators, struggle to address the complexities introduced by AI. Who owns the copyright to a piece of music composed by an AI? How can creators prove ownership and control the distribution of their work? These questions highlight the need for a new framework that can manage the unique challenges posed by AI-generated content.

Blockchain: A decentralised solution

Blockchain technology, with its decentralised and immutable nature, offers a promising solution to the challenges of AI copyright. At its core, blockchain is a distributed ledger that records transactions in a secure and transparent manner. Each block in the chain contains a timestamp and a link to the previous block, making it virtually tamper-proof. This inherent security and transparency make blockchain an ideal platform for managing digital rights.

One of the key advantages of blockchain is its ability to establish provenance and ownership. By recording the creation and subsequent transactions of digital content on a blockchain, creators can prove the originality and ownership of their work. This is particularly valuable for AI-generated content, where the line between human and machine authorship can be blurred.

Smart contracts and automated rights management

Smart contracts, self-executing contracts with the terms of the agreement directly written into code, are another powerful feature of blockchain technology that can revolutionise copyright management. These contracts can automatically enforce copyright terms, ensuring that creators are compensated for the use of their work.

Also Read: How blockchain can enhance sustainability in fashion

For instance, an AI-generated piece of music could be embedded with a smart contract that specifies the terms of its use. Whenever the music is played, the smart contract can automatically collect royalties and distribute them to the rightful owner. This not only simplifies the process of rights management but also ensures that creators receive fair compensation without the need for intermediaries.

A notable example of blockchain-based rights management is the platform Audius, a decentralised music streaming service that uses blockchain to ensure artists retain control over their music and receive fair compensation. As of May 2024, the platform has has between 5 million and 6 million monthly active users, demonstrating the potential of blockchain to disrupt traditional industries and provide new opportunities for creators.

Challenges and considerations

While blockchain technology offers significant potential for AI copyright management, it is not without challenges. One of the primary concerns is the scalability of blockchain networks. As the volume of AI-generated content grows, the blockchain must be able to handle a large number of transactions efficiently. Current blockchain networks, such as Bitcoin and Ethereum, have faced scalability issues, leading to high transaction fees and slower processing times.

However, ongoing research and development in blockchain technology are addressing these issues. Layer 2 solutions, such as the Lightning Network for Bitcoin and Ethereum’s Optimistic Rollups, aim to increase transaction throughput and reduce costs. Moreover, newer blockchain platforms like Solana and Mantle are designed with scalability in mind, offering faster and more efficient networks.

Another consideration is the legal recognition of blockchain records. While blockchain provides a secure and transparent way to record ownership and transactions, the legal system must recognise these records for them to be effective in enforcing copyright. This requires updating existing copyright laws to accommodate blockchain technology and ensure its compatibility with legal standards.

The future of blockchain and AI copyright

Despite these challenges, the future of blockchain and AI copyright management looks promising. As both technologies continue to evolve, they are likely to become increasingly integrated, providing a robust framework for protecting digital rights in the age of AI.

Also Read: 5 dimensions of responsible AI: Enhancing societal needs with blockchain

One potential development is the creation of decentralised autonomous organisations (DAOs) for content creators. These organisations, governed by smart contracts, could provide a collective platform for creators to manage their rights, distribute their work, and receive fair compensation.

For example, an AI-generated artwork could be minted as a non-fungible token (NFT) on a blockchain, with the DAO managing its sale and distribution. The creator would retain ownership and receive royalties from secondary sales, ensuring ongoing compensation for their work.

Conclusion: A personal perspective

As an observer of technological trends, I am optimistic about the potential of blockchain to address the challenges of AI copyright. The decentralised and transparent nature of blockchain provides a robust framework for managing digital rights, ensuring that creators receive fair compensation and retain control over their work. While there are challenges to overcome, the ongoing development of blockchain technology and its integration with AI offer a promising path forward.

The rise of AI-generated content presents a unique opportunity to rethink traditional copyright laws and embrace new technologies that can better serve the needs of creators in the digital age. Blockchain, with its ability to establish provenance, enforce smart contracts, and provide a decentralised platform for rights management, is well-positioned to play a central role in this transformation.

As we move forward, it is essential for policymakers, creators, and technologists to collaborate and develop a legal framework that recognises the potential of blockchain and supports its adoption for AI copyright management. By doing so, we can create a more equitable and efficient system that benefits both creators and consumers, ensuring that the digital economy continues to thrive in the age of AI.

In conclusion, the integration of blockchain and AI represents a significant step forward in the evolution of digital rights management. By leveraging the strengths of both technologies, we can create a future where creators are empowered, intellectual property is protected, and innovation is encouraged. The journey may be challenging, but the potential rewards are immense, making it a worthwhile endeavour for all stakeholders involved.

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Blockchain technology, once a niche concept, has rapidly become a transformative force across various industries. Originally designed as the underlying technology for cryptocurrencies like Bitcoin, blockchain has evolved to offer much more than digital currencies.

Its decentralised and tamper-proof nature has sparked innovation in finance, supply chain management, healthcare, and beyond. In this article, we will explore the fundamentals of blockchain technology, its key features, and its far-reaching implications for the future.

Blockchain technology has emerged as a transformative force in the world of finance, significantly impacting global payment solutions and cross-border remittance. By offering transparency, security, efficiency, and cost-effectiveness, blockchain has revolutionised the way money is transferred across borders and has the potential to reshape the entire financial industry.

In this article, we will explore the profound impact of blockchain on global payment solutions and cross-border remittance.

Understanding blockchain technology

At its core, a blockchain is a distributed ledger that records transactions across multiple computers or nodes. Here are some key components and principles of blockchain technology:

• Decentralisation: Unlike traditional systems that rely on a central authority, a blockchain operates on a network of computers, making it decentralised. This means no single entity has complete control, enhancing security and transparency.
• Immutable ledger: Once data is recorded on a blockchain, it becomes nearly impossible to alter or delete. Each new transaction is linked to the previous one, creating a chain of blocks with a complete history.
• Transparency: Information stored on a blockchain is typically visible to all participants, ensuring transparency and reducing the risk of fraud.
• Security: Blockchain employs advanced cryptographic techniques to secure data and transactions. The distributed nature of the network makes it highly resistant to hacking.
• Smart contracts: Smart contracts are self-executing agreements with predefined rules. They automatically execute when conditions are met, reducing the need for intermediaries.

Applications across industries

• Finance: Blockchain has disrupted the financial sector, offering faster, cheaper, and more secure cross-border payments. Cryptocurrencies like Bitcoin and Ethereum have introduced digital assets and decentralised finance (DeFi) platforms that enable lending, borrowing, and trading without traditional banks.
• Supply chain: In supply chain management, blockchain enhances transparency and traceability. It allows stakeholders to track products from origin to destination, reducing fraud, counterfeits, and inefficiencies.
• Healthcare: Blockchain secures health records and ensures interoperability among healthcare providers. Patients gain control over their data, and researchers can access anonymised information for medical studies.
• Voting systems: Blockchain can be used for secure and transparent electronic voting systems. It can eliminate voter fraud and ensure accurate election results.
• Real estate: Property transactions benefit from blockchain’s transparency and efficiency. It simplifies title transfers, reduces fraud, and lowers transaction costs.
• Energy: Blockchain enables peer-to-peer energy trading and grid management. Prosumers can sell excess energy to neighbours, reducing reliance on centralised utilities.

Also Read: How blockchain can enhance sustainability in fashion

Blockchain and global payment solutions

Blockchain technology has disrupted the world of finance by offering faster, cheaper, and more secure global payment solutions and cross-border remittance services. Its decentralised, transparent, and secure nature has the potential to make financial transactions more accessible to people worldwide while reducing costs and enhancing security.

As blockchain continues to evolve and overcome challenges, it will shape the future of global finance and pave the way for a more interconnected and inclusive world economy.

Blockchain technology has transformed global payment solutions in the following ways:

• Faster transactions: Traditional cross-border payments can take several days to clear. Blockchain enables near-instantaneous settlement, reducing transaction times from days to minutes or even seconds.
• Cost-effective: Traditional financial institutions often charge substantial fees for cross-border transactions. Blockchain payments are typically more cost-effective, with lower fees and competitive exchange rates.
• 24/7 availability: Blockchain operates 24/7, eliminating the constraints of banking hours and enabling continuous global payments.
• Enhanced security: Blockchain’s cryptographic security measures significantly reduce the risk of fraud and unauthorised access to payment data.
• Financial inclusion: Blockchain-based global payment solutions are accessible to individuals and businesses worldwide, including those in underserved or unbanked regions.

Blockchain and cross-border remittance

Blockchain’s impact on cross-border remittance is particularly noteworthy:

• Reduced costs: Traditional remittance services often charge high fees and offer unfavorable exchange rates. Blockchain-based remittance platforms can offer significant cost savings for senders and recipients.
• Speed and efficiency: Blockchain allows for real-time or near-real-time remittance transfers, eliminating the delays associated with traditional banking systems.
• Transparency: Blockchain’s transparency ensures that both senders and recipients can track the status of remittances, providing peace of mind.
• Security and fraud prevention: The immutable nature of blockchain records makes cross-border remittances highly secure and less susceptible to fraud.
• Financial inclusion: Blockchain-powered remittance services open up opportunities for financial inclusion, enabling access to remittances for people who lack access to traditional banking services.

Outlook of blockchain technology for global payments and cross-border remittance

While blockchain offers promising solutions for global payment and cross-border remittance, challenges remain. Scalability, regulatory compliance, and interoperability are among the key issues that need to be addressed. Additionally, user adoption and education are crucial for the widespread acceptance of blockchain-based solutions.

The future of blockchain in global payments and cross-border remittance is bright. Ongoing research and development are focused on addressing current limitations, and collaborations between the blockchain industry and financial institutions are driving innovation. As blockchain technology continues to mature, it will play an increasingly pivotal role in creating a more efficient, accessible, and secure global financial ecosystem.

While blockchain technology holds immense promise, it faces challenges. Scalability, energy consumption (especially in proof-of-work systems), regulatory hurdles, and standardisation are key issues to address. Moreover, blockchain’s mainstream adoption requires user-friendly interfaces and education.

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Editor’s note: e27 aims to foster thought leadership by publishing views from the community. Share your opinion by submitting an article, video, podcast, or infographic.

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This article was first published on August 19, 2024

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