Anthropic Unveils the Revolutionary Claude 3.7 Sonnet AI Model

Introduction to Claude 3.7 Sonnet

The unveiling of Claude 3.7 Sonnet by Anthropic marks a significant advancement in artificial intelligence, embodying the pinnacle of hybrid reasoning technology. This innovative model was designed to deliver both rapid responses and detailed, context-rich answers, setting a new standard in AI capabilities. Lauded as Anthropic's most intelligent model to date, Claude 3.7 Sonnet introduces revolutionary features such as "Standard" and "Extended" modes that accommodate diverse user needs, from swift queries to complex problem-solving scenarios.

One of the standout features of Claude 3.7 Sonnet is its self-reflection capability, a mechanism that allows the AI to evaluate its own reasoning process before delivering responses. This introspective process not only enhances the model's problem-solving capacity but also provides greater transparency, reinforcing trust with its users. Furthermore, the model's introduction of "Claude Code," a command-line tool, underscores its versatility, making strides in the realm of AI-assisted software development. The preview of Claude Code indicates a future where developers could significantly reduce coding time by offloading repetitive tasks to the AI [1].

Claude 3.7 Sonnet's "hybrid reasoning" has been a focal point of interest, allowing the AI to fluidly switch between addressing rapid questions and delving into intricately detailed tasks. This capability effectively bridges the gap between speed and depth that previous models struggled to manage, representing a paradigm shift in how AI is utilized across various fields. With applications that span from medical imaging to financial modeling, Claude 3.7 Sonnet is positioned to greatly enhance productivity and efficiency within these industries [1].

Despite the promising capabilities of Claude 3.7 Sonnet, the model does not come without its challenges. The extended mode, while providing richer responses, has been noted to be slower, which could pose limitations depending on the urgency of task requirements. Additionally, pricing structures remain a point of contention, particularly for smaller enterprises that may find the cost of input and output tokens prohibitively expensive [1]. These aspects need careful consideration by potential users when determining the model’s fit for their specific needs.

The release of Claude 3.7 Sonnet has stirred discussions about data and copyright concerns, given that the AI's development parameters prioritize enhancing reasoning over relying purely on massive data inputs. This shift aims to mitigate some of the ethical and legal challenges earlier models faced related to data usage [1]. As AI continues to evolve, the emphasis on reasoning rather than sheer data will likely become a critical focus for developers and policymakers alike.

Features of Claude 3.7 Sonnet

Claude 3.7 Sonnet marks a significant advancement in artificial intelligence by introducing the concept of "hybrid reasoning." This cutting-edge feature enables the AI model to efficiently manage both immediate, straightforward tasks as well as intricate, multifaceted challenges. Traditional AI models often required users to choose between speed and depth of response, but Claude 3.7 Sonnet eliminates this trade-off by deftly balancing rapid processing with comprehensive, thoughtful analysis. The model's dual-mode capability allows users to switch between Standard and Extended modes, catering to different requirements for efficiency and detail. Such flexibility ensures that the AI remains versatile, adapting seamlessly to a variety of tasks and industries.

One of the standout features of Claude 3.7 Sonnet is its ability to engage in self-reflection, which significantly enhances its problem-solving acumen. Before delivering responses, the AI evaluates its own reasoning process, refining outputs for greater accuracy and transparency. This self-reflective approach not only bolsters the reliability of the information provided but also aligns with the ethical considerations of artificial intelligence development. By continually assessing its decisions, Claude 3.7 Sonnet demonstrates a capacity for introspection that is rare among its peers, setting a new standard for AI accountability and performance.

Moreover, Claude 3.7 Sonnet is designed with a keen awareness of copyright and data availability issues prevalent in AI today. Instead of heavily relying on extensive datasets that might contain copyrighted material, the model emphasizes refined reasoning capabilities. This approach reduces the dependency on vast amounts of potentially sensitive data, addressing significant ethical and legal concerns regarding AI training processes. By focusing on efficient reasoning, Claude 3.7 Sonnet not only enhances its own functionality but also paves the way for more responsible AI consumption and application.

In terms of tools for software developers, Claude 3.7 Sonnet introduces Claude Code, a promising command-line utility currently in preview. This tool aims to revolutionize coding by allowing developers to delegate complex software tasks to the AI, potentially accelerating development timelines and reducing workloads. As a result, developers can achieve heightened productivity and focus on more creative aspects of software design. While Claude Code is still under refinement, its integration highlights the growing trend of AI-led innovation in programming and the potential for more efficient project management.

Claude 3.7 Sonnet’s launch is poised to redefine the competitive landscape of artificial intelligence. With its pioneering features, the model sets a new benchmark for hybrid reasoning capabilities and intensifies competition with industry giants like OpenAI and DeepSeek. This escalation prompts a renewed focus on real-world performance and the "thinking time" control AI can offer, promoting further innovation across the sector. As companies vie to integrate advanced hybrid reasoning into their offerings, consumers can expect a wave of improved AI-based solutions that promise to enhance various aspects of digital interaction.

Hybrid Reasoning Explained

In the realm of artificial intelligence, the concept of "hybrid reasoning" is gaining significant traction, especially with Anthropic's latest offering, Claude 3.7 Sonnet. Hybrid reasoning refers to the AI's ability to handle both rapid, straightforward queries and intricate, detailed tasks with equal proficiency. This capability is a notable advancement over traditional AI models that often struggle with a trade-off between speed and accuracy. With Claude 3.7 Sonnet, users can expect seamless performance, whether they are seeking quick answers or deep insights, a feature prominently highlighted by industry experts like Dr. Sarah Chen. This model exemplifies the evolution towards more sophisticated AI systems that can adaptively manage diverse tasks with precision ().

The launch of Claude 3.7 Sonnet underscores a strategic shift in AI development towards models that integrate hybrid reasoning. By accommodating both standard and extended modes, Anthropic has positioned its latest model as a versatile tool that enhances problem-solving through self-reflection. This self-reflection mechanism allows the AI to review its reasoning processes before finalizing responses, thereby increasing accuracy and transparency in its interactions (). Such features not only improve user experience but also position Claude 3.7 as a leader in the AI space, capable of meeting complex demands in fields ranging from healthcare to finance.

Claude 3.7 Sonnet's hybrid reasoning ability also addresses pressing concerns surrounding copyright and data usage. By focusing on refining reasoning pathways rather than solely relying on expansive datasets, Anthropic aims to mitigate the ethical and legal challenges that accompany AI training. This nuanced approach not only aligns with emerging AI safety standards but also fosters greater trust among users concerned about data privacy ().

Moreover, the AI landscape is becoming increasingly competitive, with Claude 3.7 Sonnet taking center stage against formidable contenders like OpenAI and DeepSeek. This competition is driving rapid innovation in AI development, as highlighted by Anthropic's strategic emphasis on hybrid reasoning. The attention to real-world performance and control over "thinking time" is part of Anthropic's broader goal to redefine AI efficiency and applicability in various domains. In doing so, Claude 3.7 Sonnet not only demonstrates superior intellectual capabilities but also sets a new benchmark for AI models aspiring to combine speed with comprehensive reasoning ().

The community response to these innovations has been predominantly positive, with users praising Claude 3.7 Sonnet as "INSANELY GOOD." Its dual capability to manage both basic and complex tasks effectively positions it as a revolutionary tool for productivity enhancements in various industries, such as medical imaging and financial modeling. However, conversations in tech forums also highlight accessibility challenges due to the pricing model and the non-open-source nature of Claude Code, reflecting ongoing debates about democratization and transparency in AI technology ().

Self-Reflection Capabilities

Self-reflection capabilities mark a transformative element in the design of modern AI models, such as Anthropic's Claude 3.7 Sonnet. This feature facilitates the AI's ability to analyze its own reasoning process, thereby enhancing the accuracy and transparency of its responses. By continuously re-evaluating the logic and data used in generating responses, Claude 3.7 Sonnet is positioned to mitigate errors and refine its problem-solving approaches. This self-assessment mechanism not only improves the model's output but also builds user confidence by offering a clearer glimpse into the AI’s decision-making process. More details on the launch and capabilities of Claude 3.7 Sonnet can be found in the official announcement by Anthropic.

The integration of self-reflection capabilities in AI systems like Claude 3.7 Sonnet by Anthropic is a significant stride towards creating more autonomous and sophisticated machine learning models. Unlike previous iterations of AI that processed inputs and delivered outputs without introspection, Claude 3.7 Sonnet is engineered to internally critique its own logic and assumptions before finalizing an answer. This internal feedback loop plays a crucial role in managing complex tasks and delivering nuanced answers that consider broader contexts and potential biases inherent in training data. Such advancements reflect Anthropic's commitment to pushing the boundaries of what AI can accomplish by incorporating checks and balances within the AI itself, thus boosting its utility and ethical deployment. For further insights, the Business World article provides a comprehensive overview.

Comparison with Previous Models

Claude 3.7 Sonnet represents a significant leap from Anthropic's previous models, incorporating several advanced features that enhance its reasoning capabilities. Unlike earlier iterations, this model introduces "hybrid reasoning" which enables it to deliver both rapid responses for straightforward inquiries and in-depth analyses for complex problems. This dual capability marks a departure from the traditional models that often required a compromise between speed and accuracy. By embedding self-reflective processes, Claude 3.7 Sonnet enhances decision-making transparency and reduces errors prior to reaching conclusions, an advancement from former models that lacked such introspective functionality [1](https://www.businessworld.in/article/anthropic-unveils-claude-37-sonnet-introducing-hybrid-reasoning-ai-549263).

In comparison to its predecessors, Claude 3.7 Sonnet offers more versatility through its Standard and Extended modes. While previous Anthropic models primarily focused on a singular mode of operation, this version provides users with the option to choose between quick, surface-level interaction and deep, prolonged engagement. This adaptability is a testament to Anthropic's innovative strides in AI, which aim to optimize user experience by catering to different application needs. Furthermore, the model's self-reflection capability signifies a foundational shift towards greater user confidence, as it reviews its reasoning process before finalizing answers, thus improving error detection and fostering user trust [1](https://www.businessworld.in/article/anthropic-unveils-claude-37-sonnet-introducing-hybrid-reasoning-ai-549263).

The introduction of Claude Code is another distinguishing feature of Claude 3.7 Sonnet, showcasing a direct enhancement over past models. This command-line tool, currently in preview, allows developers to integrate AI into the software development process, potentially increasing coding efficiency and reducing time constraints. This advancement indicates Anthropic's intent to extend the applicability of its models beyond generic AI applications to more specialized fields like software engineering. Earlier models, which did not have such capabilities, are now rendered less equipped for the evolving demands of AI-assisted coding and automation [1](https://www.businessworld.in/article/anthropic-unveils-claude-37-sonnet-introducing-hybrid-reasoning-ai-549263).

One of the key issues that past models encountered was the handling of copyrighted material and reliance on expansive datasets, which often sparked ethical concerns. Claude 3.7 Sonnet addresses these challenges by focusing on enhancing reasoning skills rather than depending heavily on vast data inputs. This strategic shift not only distinguishes it from previous iterations by prioritizing ethical compliance but also aligns with modern expectations for transparent and secure AI usage. This focus on reasoning rather than rote data consumption presents a progressive approach to mitigating copyright issues and establishing greater user trust [1](https://www.businessworld.in/article/anthropic-unveils-claude-37-sonnet-introducing-hybrid-reasoning-ai-549263).

Compared to previous models, Claude 3.7 Sonnet has also been specifically designed to perform competitively in the AI market, particularly targeting rivals such as OpenAI and DeepSeek. By emphasizing real-world performance and providing control over "thinking time," this model aims to secure a strong foothold in the competitive landscape of AI technology. The competitive edge offered by its hybrid reasoning approach not only elevates the model above its predecessors but also challenges competitors to rethink their strategies in both speed and reasoning quality in artificial intelligence [7](https://venturebeat.com/ai/anthropics-claude-3-7-sonnet-takes-aim-at-openai-and-deepseek-in-ais-next-big-battle/).

Claude Code: AI-Assisted Coding

Claude Code, an innovative tool introduced by Anthropic, is poised to redefine the landscape of AI-assisted coding. Central to this revolution is Claude 3.7 Sonnet, Anthropic's latest AI model, boasting sophisticated hybrid reasoning capabilities as detailed in a recent BusinessWorld article. This model is engineered to handle both simple and complex tasks efficiently, marking a significant leap from previous iterations. By integrating command-line functionalities, Claude Code empowers developers to leverage AI in writing and debugging code more effectively, ultimately enhancing productivity.

Addressing Copyright and Data Concerns

In the rapidly evolving field of artificial intelligence, addressing copyright and data concerns has become a critical focus for developers and policymakers alike. The unveiling of Anthropic's Claude 3.7 Sonnet, as detailed in a [Business World article](https://www.businessworld.in/article/anthropic-unveils-claude-37-sonnet-introducing-hybrid-reasoning-ai-549263), marks a significant step towards resolving these issues. By concentrating on enhancing reasoning capabilities, Claude 3.7 Sonnet minimizes its reliance on vast datasets, thereby reducing the need to use potentially copyrighted content extensively. This strategic focus aims to alleviate concerns surrounding the unauthorized use of copyrighted materials, providing a more ethical approach to AI development.

Claude 3.7 Sonnet's innovative approach also highlights important data availability issues. Traditional AI models often depend on large datasets, which can pose challenges related to data privacy and security. However, by utilizing its hybrid reasoning ability, Claude 3.7 Sonnet addresses these concerns more effectively. As this model allows for both quick and detailed responses, it streamlines data usage, ensuring that only the necessary information is processed and stored. This optimization not only supports better data management practices but also aligns with growing calls for transparency and ethical standards in AI operations.

The integration of sophisticated reasoning methods in Claude 3.7 Sonnet signifies a paradigm shift in handling copyright and data concerns. By leveraging hybrid reasoning, the model operates with a focus on reasoning processes rather than sheer data consumption. This aligns well with current discussions in the tech community, which emphasize the importance of balancing AI capabilities with ethical considerations. As industries increasingly adopt AI technologies, models like Claude 3.7 Sonnet could set new benchmarks for responsible AI use, ensuring progress while safeguarding intellectual property rights and data protection.

As AI developers like Anthropic continue to prioritize ethical development, models such as Claude 3.7 Sonnet can pave the way for more robust AI ecosystems. The model's ability to self-reflect, a feature highlighted in its release, enables it to refine its reasoning processes internally. This aspect not only enhances its problem-solving capabilities but also ensures compliance with copyright laws and data handling regulations, a point underscored by the ongoing discussions in [Bloomberg Law](https://www.bloomberglaw.com/external/document/X4H9CFB4000000/copyrights-professional-perspective-ip-issues-with-ai-code-gener). It is this forward-thinking approach that signifies the potential for Claude 3.7 Sonnet and similar models to redefine the landscape of AI ethics.

Limitations and Challenges

Despite its advanced capabilities, Anthropic’s Claude 3.7 Sonnet faces several limitations and challenges inherent to AI technology. One notable challenge is the model's slower response times when operating in Extended Mode. This delay can hinder user experience, especially in applications requiring real-time interaction [1](https://www.businessworld.in/article/anthropic-unveils-claude-37-sonnet-introducing-hybrid-reasoning-ai-549263).

Another significant challenge for Claude 3.7 is its pricing, which may restrict accessibility to smaller businesses. At $3 per million input tokens and $15 per million output tokens, some organizations may find it cost-prohibitive, despite its advanced functionalities [4](https://opentools.ai/news/anthropics-claude-37-sonnet-a-game-changer-in-ai-hybrid-reasoning). This financial barrier underscores a broader issue in AI democratization, where high operating costs limit the technology's broader adoption.

Furthermore, Claude 3.7's reliance on copyrighted material for training raises ethical concerns. The opacity in its data handling practices, coupled with the lack of open-source transparency, has sparked debates over its ethical implications [3](https://medium.com/@mirzasamaddanat/anthropics-claude-3-7-a-leap-forward-in-ai-with-hybrid-reasoning-8911c109cd11). Addressing these concerns is essential to fostering a more secure and ethically sound AI ecosystem.

The hybrid reasoning capabilities of Claude 3.7, while groundbreaking, also introduce complexity regarding algorithmic transparency. Users and developers demand clarity on how these processes work to ensure fairness and unbiased output. This need for transparency is critical, particularly in sensitive sectors such as healthcare and finance, where biased AI decision-making could have severe repercussions.

Finally, the competitive landscape with AI giants like OpenAI and DeepSeek adds pressure on Anthropic to consistently innovate and refine its models. This environment not only pushes for rapid advancements but also necessitates robust testing to ensure reliability before commercial deployment [7](https://venturebeat.com/ai/anthropics-claude-3-7-sonnet-takes-aim-at-openai-and-deepseek-in-ais-next-big-battle/). This balancing act of innovation and reliability presents an ongoing challenge for AI developers.

How to Access Claude 3.7 Sonnet

Accessing Claude 3.7 Sonnet, Anthropic's latest AI model, involves understanding its unique features and integration capabilities. As of the release captured in a comprehensive [Business World article](https://www.businessworld.in/article/anthropic-unveils-claude-37-sonnet-introducing-hybrid-reasoning-ai-549263), the model is available through an API designed primarily for developers. This enables seamless integration into existing systems, allowing businesses and researchers to leverage its "hybrid reasoning" capabilities, which facilitate both quick responses and detailed analytical tasks.

To access the Claude 3.7 Sonnet, interested developers and organizations should first visit Anthropic's official website or contact their sales department for detailed onboarding instructions and pricing information. The model is structured to cater to a broad range of applications, from rapid real-time analytics to complex problem-solving scenarios. One of its key advantages is the dual modes of operation, providing Standard and Extended modes depending on the nature of the task, as demonstrated in their official announcement [here](https://www.anthropic.com/news/claude-3-7-sonnet).

For those in academia or industries heavily reliant on AI, delving into the Claude 3.7 Sonnet's self-reflection capabilities is invaluable. This feature is particularly beneficial in fields requiring high accuracy and reliability because the model reviews its own reasoning processes to enhance outputs. According to reports, this functionality is critical in improving transparency and problem-solving efficiency, making it a standout tool in the market.

Given its anticipated impact, accessing Claude 3.7 Sonnet offers strategic advantages, especially in areas like AI-driven software development and data analysis. The Claude Code, which is still in preview, represents a significant leap in AI-assisted coding, and aligning with Anthropic's product roadmap could provide a competitive edge. As articulated by experts like Dr. Sarah Chen, this model could redefine benchmarks in hybrid reasoning capabilities.

Market Competition and AI Model Race

The race to develop the most advanced AI model has intensified the competition among leading tech giants, with companies like Anthropic, OpenAI, and DeepSeek at the forefront. Anthropic's recent launch of Claude 3.7 Sonnet marked a significant leap in AI capabilities, particularly with its integrated **hybrid reasoning** feature. This feature allows the model to adapt its approach to various tasks, excelling in both rapid responses and complex problem-solving scenarios. As these companies strive to outdo each other, the emphasis is increasingly placed on not just the speed and accuracy of AI models, but also their ability to integrate nuanced understanding and ethical considerations. New AI models are being judged not only by their technical prowess but also by how they balance performance with transparency and data integrity [7].

The release of Claude 3.7 Sonnet emphasizes the strategic shift towards AI systems that can manage comprehensive tasks while maintaining remarkable efficiency. This model boasts capabilities such as self-reflection, which enhances problem-solving by enabling the model to review its reasoning before finalizing responses. As these technological advancements unfold, companies are exploring methods to integrate these models into real-world applications, providing meaningful impacts across sectors from healthcare to finance. The pressure to innovate has forced rapid advancements not only in AI technology itself but also in ethical AI practices, as developers seek to ensure their models are not only powerful but responsible as well [4].

Anthropic's innovative approach in its Claude 3.7 Sonnet model is expected to serve as a catalyst for more aggressive developments in AI. With its hybrid reasoning capability, Claude 3.7 Sonnet represents a substantial evolution from the speed/accuracy trade-offs typical in earlier AI models. This advancement has set a new benchmark that competitors will likely seek to emulate or surpass. The ongoing rivalry among AI developers has implications for the broader market as well, potentially leading to reduced costs for AI services and increased accessibility to sophisticated AI capabilities for various industries. However, as competition heats up, it remains crucial for companies to navigate the challenges related to data usage, copyright issues, and ensuring their AI models operate within ethical boundaries [1].

As Anthropic's Claude 3.7 Sonnet gains traction, the competitive landscape becomes increasingly dynamic, encouraging both innovation and collaboration among AI developers. The model's unique capabilities in hybrid reasoning have not only challenged existing AI frameworks but have also prompted introspection within the industry concerning best practices and the ethical implications of such advanced technologies. This has led to a heightened focus on AI safety and regulatory standards, as stakeholders across the tech sector work toward establishing guidelines that ensure the responsible deployment of AI technologies globally. In this context, industry leaders are recognizing the potential of international cooperation to address these challenges while promoting advancements that benefit societies worldwide [4].

Despite the promising opportunities that accompany the development of cutting-edge AI models like Claude 3.7 Sonnet, there are still significant hurdles to navigate. The model's pricing structure, for instance, raises concerns about equitable access, particularly for smaller companies that may find it challenging to afford such technologies. Furthermore, discussions within the tech community have highlighted the need for greater transparency in AI models' performance metrics and their training data. As competition continues to drive innovation, it is imperative for developers to balance technical advancements with ethical considerations, ensuring that AI progression does not exacerbate existing inequalities or introduce new ethical dilemmas. The success of these AI models will increasingly depend on their ability to integrate innovation with accountability and inclusivity [10].

Public and Expert Reactions

The launch of Claude 3.7 Sonnet by Anthropic has generated a wide array of reactions within both the public sphere and among AI experts. Enthusiasts on platforms like Reddit have been quick to applaud the AI for its advanced hybrid reasoning capabilities, which accommodate both rapid responses and intricate problem-solving tasks. This adaptability of Claude 3.7 Sonnet is seen as a boon for productivity in sectors such as healthcare, particularly in medical imaging, and in financial services for detailed modeling tasks. However, some users have raised concerns over the pricing model, which could potentially restrict smaller entities from accessing this advanced technology—currently set at a fee of $3 per million input tokens and $15 for output tokens .

Despite these cost-related concerns, the model's success is underlined by its score on various benchmarks, such as a 96.2% score on the MATH benchmark, which further cements Claude 3.7 Sonnet's reputation as a game-changer in AI hybrid reasoning. Yet, discussions persist on platforms like Hacker News regarding the non-open-source nature of Claude Code and transparency issues concerning performance metrics and underlying data processing practices. Skeptics argue that the lack of open-source availability limits the collaborative potential and scrutiny necessary for community-driven improvements .

In terms of expert feedback, Claude 3.7 Sonnet has been met with an optimistic albeit cautious reception. Dr. Sarah Chen commends its ability to maintain context throughout interactions, a significant marker for advancements in hybrid reasoning capabilities, while Professor Michael Thompson highlights the notable improvement in synthesizing information. Despite these advances, Thompson advises a careful testing period prior to its widespread integration . Ethical concerns are also broached by Dr. Rachel Martinez, who stresses the importance of evaluating the implications of the AI's decision-making processes in real-world applications.

Future Implications: Economic, Social, and Political Impact

The launch of Claude 3.7 Sonnet signifies a major advancement in AI technology, potentially reshaping global economics. Anthropic's innovative model could democratize AI access with competitive pricing, fostering widespread innovation across various industries. By enhancing efficiency in software development and complex analysis, Claude 3.7 Sonnet may significantly boost productivity in sectors ranging from finance to healthcare. However, as AI technologies continue to advance, there could be an increase in job displacement, especially in roles where automation can surpass human capability. Moreover, as the competition intensifies among major AI players like OpenAI and DeepSeek, this could lead to rapid innovation, driving down costs and accelerating the development of new AI services [5] [8], [4].

Socially, Claude 3.7 Sonnet could revolutionize education and training by making advanced thinking more accessible, potentially lowering barriers to learning and fostering deeper understanding. The "extended thinking mode" offers students and professionals alike an opportunity to engage with content on a deeper level, promoting problem-solving skills that are crucial in today's dynamic world. However, this advancement also brings about concerns regarding digital equity. With AI widening the digital divide, there is a growing necessity for AI literacy and specialized training programs aimed at equipping individuals with the skills needed to thrive in this new era. Inequities in access to technology could be exacerbated if educational resources remain unbalanced, highlighting the need for inclusive strategies to manage these changes [2], [8].

Politically, the emergence of Claude 3.7 Sonnet underscores the urgent need for comprehensive AI regulations and ethical guidelines. Countries may face heightened geopolitical tensions as they vie for dominance in AI development, prompting the necessity of international collaborations to establish safety and ethical usage standards. Moreover, the focus on securing AI systems against misuse and misinformation is critical, especially as AI's role in information dissemination grows. With the EU potentially setting global precedents in AI safety standards, the political landscape surrounding AI technology may become more collaborative yet competitive, requiring ongoing dialogue and strategic policy-making to ensure that advancements benefit all of society [4], [5], [10].