Andrew Ng, the Founder of Deeplearning.ai and former Co-Founder of Google Brain and Chief Scientist at Baidu, explores the fundamental aspects of responsible AI through his Generative AI course. Within this discourse, the significance of data, particularly large datasets, in constructing expansive language models like Chat GPT and Bard becomes strikingly apparent.
In examining the sourcing and governance of this data, pertinent questions arise: Where does this data originate? Who regulates its flow? And how do businesses discern the inputs essential for optimising real-world applications? These inquiries resonate with practitioners in the realm of responsible AI, where the focus extends beyond mere technical prowess to encompass ethical considerations and societal impact.
By leveraging blockchain’s decentralised framework, coupled with transparent and reliable data streams from verified sources, companies of all sizes are redefining access to information. This democratisation of data not only fosters a more inclusive ecosystem but also reshapes the dynamics of how information is utilised across sectors.
Why does society need responsible AI?
This will be immediately obvious to those who study or work with large language models, but the implications of how these models are developed have yet to reach the mainstream. What the public is familiar with today is the noise around AI investments, the potential of AI to obliterate jobs, and the danger of AI clouding our judgements as the public is fed streams of fake news. However, the value of AI and the repercussions around implementation don’t make sense without first considering the approach to development.
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Blockchain technology has a role to play in addressing ethical concerns and advancing the principles of responsible development outlined by Ng: fairness, transparency, privacy, security, and ethical use.
Let’s examine how blockchain contributes to each dimension of responsible AI.
Fairness
Bias in AI algorithms can stem from skewed or inadequate data sets, leading to discriminatory outcomes. Blockchain technology offers a decentralised and immutable ledger that transparently records data transactions.
By leveraging blockchain for data collection and storage, developers can ensure the integrity and diversity of data sets used for training AI models.“Flare allows applications to leverage diverse data sources. This enables businesses to make data-driven decisions and execute actions based on real-world events. The native protocol eliminates the need for third-party data oracle solutions, ensuring a highly decentralised and cost-effective infrastructure for accessing external data, ”says Nick Camion, Head of Marketing for Flare Network.
Transparency
Blockchain’s tamper-proof nature enhances the transparency of AI systems by providing an auditable record of data transactions and algorithmic processes. Through blockchain-based data provenance, stakeholders can trace the origins and transformations of data inputs, ensuring accountability and facilitating algorithmic transparency. Projects like Flare and SingulatityNET are driving access to data and the sharing of innovative AI capabilities using blockchain technology.
Privacy
Privacy-preserving techniques are crucial for safeguarding sensitive data in AI systems. Blockchain technology offers cryptographic solutions such as zero-knowledge proofs that enable privacy-preserving computations while maintaining data integrity.
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Security
Smart contracts deployed on blockchain platforms can enforce access control policies and automate security measures, ensuring the resilience and robustness of AI systems against cyber threats and adversarial attacks. “We need the cost to disrupt the data supply to be greater than the benefit of doing so. Decentralised data access is far harder to disrupt, supporting the secure management of significantly greater value,” says Campion.
Ethical use
Ethical considerations in AI development include societal impacts, human well-being, and responsible governance. Blockchain technology facilitates decentralised governance models through consensus mechanisms and decentralised autonomous organisations (DAOs), enabling transparent and participatory decision-making in AI development and deployment.
Incorporating blockchain technology into AI development and deployment processes holds promise for advancing the five dimensions of responsible AI. As we navigate the ethical landscape of AI, the integration of blockchain offers a pathway towards a more equitable, transparent, and responsible AI-driven future.
The responsible use of AI is no longer a choice but a necessity for corporations of all sizes. As AI becomes increasingly integrated into business operations, from customer service chatbots to predictive analytics for decision-making, the ethical implications of AI deployment come to the forefront.
Consumers, stakeholders, and regulatory bodies will continue to demand more transparency in AI practices, and unethical AI deployment can lead to reputational damage and long-term financial repercussions for businesses.
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This article was first published on March 4, 2024
The post 5 dimensions of responsible AI: Enhancing societal needs with blockchain appeared first on e27.