Augmented Intelligence vs. Artificial Intelligence: Understanding the Differences and Applications

In the rapidly evolving world of technology, Artificial Intelligence (AI) and Augmented Intelligence (AI) are two terms that often surface. While they may seem similar, they represent distinct concepts with unique applications and implications. This article delves into the definitions, differences, benefits, challenges, and future trends of Augmented Intelligence and Artificial Intelligence, providing a clear understanding of each.

What are Augmented Intelligence and Artificial Intelligence, and How Do They Differ?

Artificial Intelligence (AI) refers to the development of computer systems that can perform tasks typically requiring human intelligence. These tasks include learning, reasoning, problem-solving, perception, and language understanding. AI aims to create machines that can operate autonomously and make decisions without human intervention.

Augmented Intelligence, also known as Intelligence Amplification (IA), focuses on enhancing human intelligence through the use of technology. Instead of replacing humans, augmented intelligence systems are designed to work alongside them, providing tools and insights that aid in decision-making and problem-solving.

Key Differences Between Augmented Intelligence and Artificial Intelligence

How Do Augmented Intelligence and Artificial Intelligence Work Together in Modern Technology?

Augmented Intelligence and Artificial Intelligence often complement each other in modern technological applications. While AI can handle complex computations and data processing, augmented intelligence provides the necessary tools for humans to interpret and utilize this information effectively.

Artificial Intelligence Integration

AI integrates into various systems to perform tasks such as data analysis, pattern recognition, and automation. For instance, in healthcare, AI algorithms can analyze medical images to detect anomalies that the human eye may miss.

Augmented Intelligence Enhancement

Augmented intelligence systems take the outputs generated by AI and present them in a way that is understandable and actionable for humans. Continuing the healthcare example, augmented intelligence tools can help doctors interpret AI-generated insights, allowing them to make more informed decisions regarding patient care.

What Are the Core Components of Artificial Intelligence Compared to Augmented Intelligence?

Understanding the core components of both AI and augmented intelligence helps in distinguishing their functionalities and applications.

Core Components of Artificial Intelligence

1. Machine Learning (ML): Enables systems to learn from data and improve over time without explicit programming.
2. Natural Language Processing (NLP): Allows machines to understand and interpret human language.
3. Computer Vision: Enables machines to interpret and make decisions based on visual inputs.
4. Robotic Process Automation (RPA): Automates routine and repetitive tasks.
5. Deep Learning: A subset of ML that uses neural networks with many layers to analyze various data factors.

Core Components of Augmented Intelligence

1. Human-Centric Design: Focuses on creating tools that complement and enhance human abilities.
2. Decision Support Systems: Provides humans with data-driven insights to aid in decision-making.
3. User Interfaces: Develop intuitive interfaces that facilitate easy interaction between humans and machines.
4. Collaborative Tools: Enhances teamwork and information sharing through technology.
5. Contextual Understanding: Incorporates context to provide relevant and actionable information to users.

What Are the Key Benefits of Integrating Augmented Intelligence Over Solely Using Artificial Intelligence?

Integrating augmented intelligence offers several advantages, especially in scenarios where human judgment and creativity are crucial. Here are the key benefits:

Enhanced Decision-Making

Augmented intelligence provides humans with comprehensive data analysis and insights, enabling more informed and effective decision-making processes.

Improved Productivity

By handling routine and time-consuming tasks, augmented intelligence allows humans to focus on more strategic and creative aspects of their work.

Better User Experience

Augmented intelligence systems are designed with user-centric interfaces, ensuring that the technology is accessible and beneficial to the end-users without overwhelming them.

Increased Adaptability

Augmented intelligence can adapt to various contexts and changing environments, providing flexible support that caters to specific human needs.

Higher Accuracy and Efficiency

Combining AI’s computational power with human intuition results in higher accuracy and efficiency in tasks such as data analysis, problem-solving, and innovation.

How Do Applications of Augmented Intelligence Differ Across Industries Compared to Artificial Intelligence?

Both augmented intelligence and artificial intelligence have diverse applications across various industries. However, their roles and implementations differ based on the needs and objectives of each sector.

Healthcare

• Artificial Intelligence: AI is used for diagnosing diseases, analyzing medical images, and predicting patient outcomes through predictive analytics.
• Augmented Intelligence: AI-enhanced tools assist doctors in interpreting diagnostic results, planning treatments, and managing patient care more effectively.

Finance

• Artificial Intelligence: AI systems automate trading, detect fraudulent activities, and manage large-scale data for financial analysis.
• Augmented Intelligence: Financial analysts use AI-generated insights to make investment decisions, manage risks, and personalize customer services.

Manufacturing

• Artificial Intelligence: AI optimizes production processes, predicts maintenance needs, and controls autonomous robots in manufacturing lines.
• Augmented Intelligence: Human operators collaborate with AI tools to monitor production efficiency, troubleshoot issues, and innovate product designs.

Education

• Artificial Intelligence: AI personalizes learning experiences, automates grading, and provides virtual tutoring.
• Augmented Intelligence: Educators utilize AI-driven data to tailor teaching methods, engage with students more effectively, and enhance curriculum development.

Retail

• Artificial Intelligence: AI powers recommendation engines, manages inventory, and automates customer service through chatbots.
• Augmented Intelligence: Retail managers use AI insights to optimize store layouts, personalize marketing strategies, and improve customer engagement.

What Are the Potential Challenges of Implementing Augmented Intelligence Compared to Artificial Intelligence?

While both augmented intelligence and artificial intelligence offer substantial benefits, they also come with their own set of challenges.

Challenges of Implementing Artificial Intelligence

1. High Implementation Costs: Developing and deploying AI systems can be expensive and require significant technological and expertise investments.
2. Data Privacy Concerns: AI systems often require vast amounts of data, raising concerns about privacy and security.
3. Lack of Skilled Personnel: There is a shortage of AI development and maintenance professionals.
4. Bias and Fairness: AI algorithms can inadvertently perpetuate biases in the training data, leading to unfair outcomes.
5. Complexity and Integration: Integrating AI with existing systems can be complex and time-consuming.

Challenges of Implementing Augmented Intelligence

1. User Adoption: Ensuring that users are willing and able to adopt augmented intelligence tools can be challenging, especially if they resist change.
2. Design and Usability: Creating user-friendly interfaces that effectively enhance human capabilities requires careful design and testing.
3. Dependence on Human Input: Augmented intelligence relies on human input and interaction, which can limit its effectiveness if not properly managed.
4. Data Integration: Combining data from various sources to provide meaningful insights can be complex.
5. Balancing Automation and Control: Finding the right balance between automated processes and human control is crucial to avoid over-reliance on technology.

How Do Ethical Considerations Differ Between Augmented Intelligence and Artificial Intelligence?

Ethical considerations are paramount in the development and deployment of both augmented intelligence and artificial intelligence. However, their focus differs based on their respective roles.

Ethical Considerations in Artificial Intelligence

1. Bias and Fairness: Ensuring AI systems do not perpetuate or amplify existing biases in data.
2. Transparency: Making AI decision-making processes understandable and transparent to users.
3. Accountability: Determining who is responsible for AI-driven decisions and outcomes.
4. Privacy: Protecting the privacy of individuals whose data is used by AI systems.
5. Autonomy: Addressing the implications of autonomous systems making decisions without human intervention.

Ethical Considerations in Augmented Intelligence

1. Human Oversight: Ensuring that humans retain control over AI-enhanced decision-making processes.
2. Empowerment vs. Replacement: Balancing the enhancement of human capabilities without aiming to replace human roles.
3. Privacy and Data Security: Protecting the data used to augment human intelligence and ensuring it is not misused.
4. Accessibility: Making augmented intelligence tools accessible to all users, regardless of their technical expertise.
5. Informed Consent: Ensuring that users are aware of how augmented intelligence tools utilize their data and assist them.

What are the future trends in augmented intelligence and artificial intelligence?

The future of augmented and artificial intelligence is promising, with advancements poised further to integrate technology into various aspects of life and work.

Future Trends in Artificial Intelligence

1. Advanced Machine Learning: Improvements in machine learning algorithms will enhance AI’s ability to learn and adapt from data.
2. AI in Everyday Devices: Increased integration of AI into consumer electronics, making smart devices more intuitive and responsive.
3. Autonomous Systems: Expansion of autonomous vehicles, drones, and robotics in various industries.
4. AI Ethics and Governance: Enhanced focus on developing ethical guidelines and governance frameworks for AI deployment.
5. Quantum Computing and AI: Leveraging quantum computing to solve complex AI problems faster and more efficiently.

Future Trends in Augmented Intelligence

1. Enhanced Human-AI Collaboration: Developing more seamless collaboration tools that integrate AI insights into human workflows.
2. Personalized Augmentation: Tailoring augmented intelligence systems to individual user preferences and needs for more effective assistance.
3. Augmented Reality (AR) Integration: Combining augmented intelligence with AR to create immersive and interactive user experiences.
4. Health and Wellness: Using augmented intelligence to support mental health, personal development, and wellness initiatives.
5. Education and Training: Enhancing educational tools with augmented intelligence to provide personalized learning experiences and support educators.

How Can Organizations Effectively Implement Augmented Intelligence Compared to Artificial Intelligence?

Implementing augmented intelligence and artificial intelligence requires strategic planning and consideration of their distinct purposes and applications. Here’s how organizations can effectively implement each:

Implementing Artificial Intelligence

1. Identify Clear Objectives: Determine specific goals that AI can help achieve, such as automating tasks or improving data analysis.
2. Invest in Data Infrastructure: Ensure that there is a robust data collection, storage, and processing infrastructure to support AI initiatives.
3. Hire Skilled Professionals: Employ experts in AI development, data science, and machine learning to build and maintain AI systems.
4. Start with Pilot Projects: Begin with small-scale AI projects to test feasibility, gather insights, and refine approaches before scaling up.
5. Ensure Ethical Compliance: Develop and adhere to ethical guidelines to address biases, transparency, and accountability in AI systems.
6. Integrate with Existing Systems: Seamlessly integrate AI solutions with current business processes and technological infrastructures.
7. Continuous Monitoring and Improvement: Regularly assess AI performance and make necessary adjustments to enhance effectiveness and accuracy.

Implementing Augmented Intelligence

1. Focus on Human-Centric Design: Design systems that prioritize user experience and effectively complement human skills and roles.
2. Identify Key Areas for Enhancement: Determine areas where augmented intelligence can significantly aid human decision-making and productivity.
3. Provide Adequate Training: Train employees to effectively use and interact with augmented intelligence tools, ensuring they are comfortable and proficient.
4. Promote Collaboration: Foster a collaborative environment where humans and AI can work together seamlessly, sharing insights and responsibilities.
5. Ensure Data Accessibility and Quality: Provide access to high-quality data that can be used by augmented intelligence systems to generate meaningful insights.
6. Encourage Feedback and Iteration: Collect user feedback to continuously improve augmented intelligence tools and adapt them to evolving needs.
7. Maintain Ethical Standards: Uphold ethical practices to ensure that augmented intelligence enhances human capabilities without compromising privacy or fairness.

What Are Real-World Examples of Augmented Intelligence and Artificial Intelligence in Action?

Understanding real-world applications helps in grasping how augmented intelligence and artificial intelligence operate differently across various sectors.

Artificial Intelligence Examples

1. Autonomous Vehicles: Self-driving cars use AI to navigate roads, interpret traffic signals, and make real-time driving decisions.
2. Virtual Assistants: AI-powered assistants like Siri and Alexa process natural language to perform tasks and answer queries.
3. Predictive Maintenance: AI systems in manufacturing predict equipment failures before they occur, reducing downtime and maintenance costs.
4. Fraud Detection: Financial institutions use AI to detect unusual transaction patterns and prevent fraudulent activities.
5. Language Translation: AI-driven translation services like Google Translate convert text from one language to another with increasing accuracy.

Augmented Intelligence Examples

1. Decision Support Systems in Healthcare: Doctors use AI-enhanced tools to interpret medical data and make informed treatment decisions.
2. Financial Advisory Tools: Financial analysts leverage AI-driven insights to guide investment strategies and risk management.
3. Collaborative Robots (Cobots): In manufacturing, cobots work alongside human workers to enhance productivity and safety.
4. Educational Platforms: Teachers use augmented intelligence systems to personalize learning experiences and track student progress.
5. Customer Relationship Management (CRM) Systems: Sales professionals use AI-enhanced CRM tools to better understand customer needs and improve service delivery.

How Do Augmented Intelligence and Artificial Intelligence Impact Workforce Dynamics Differently?

Augmented and artificial intelligence significantly influence workforce dynamics, but in distinct ways.

Impact of Artificial Intelligence on the Workforce

1. Job Automation: AI automates routine and repetitive tasks, potentially reducing the need for certain job roles.
2. Skill Shifts: There is an increasing demand for skills related to AI development, data analysis, and machine learning.
3. Job Creation: New roles emerge in AI management, maintenance, and ethical oversight.
4. Productivity Enhancement: AI increases overall productivity by handling complex computations and data-driven tasks.
5. Workforce Displacement: Some workers may face displacement due to AI automation, necessitating reskilling and upskilling initiatives.

Impact of Augmented Intelligence on the Workforce

1. Enhanced Collaboration: Augmented intelligence fosters collaboration between humans and machines, enhancing overall productivity.
2. Skill Augmentation: Employees can leverage AI tools to enhance their existing skills and take on more strategic tasks.
3. Job Enrichment: Roles become more engaging as AI handles mundane tasks, allowing workers to focus on creative and complex problem-solving.
4. Continuous Learning: Workers need to adapt to new technologies and continuously learn to use augmented intelligence tools effectively.
5. Empowerment: Augmented intelligence empowers employees by providing them with better tools and insights to perform their jobs more effectively.

What Are the Key Technologies Driving Augmented Intelligence and Artificial Intelligence?

Several technologies underpin augmented and artificial intelligence functionalities, driving their advancements and applications.

Key Technologies in Artificial Intelligence

1. Machine Learning (ML): Enables systems to learn from data and improve their performance over time.
2. Deep Learning: A subset of ML that uses neural networks with many layers to analyze complex data.
3. Natural Language Processing (NLP): Allows machines to understand and interpret human language.
4. Computer Vision: Enables machines to interpret and make decisions based on visual inputs.
5. Robotic Process Automation (RPA): Automates repetitive tasks by mimicking human actions.
6. Reinforcement Learning: A type of ML where agents learn by interacting with their environment and receiving feedback.

Key Technologies in Augmented Intelligence

1. Human-Centric AI Design: Focuses on creating AI systems that enhance human capabilities and are easy to interact with.
2. Decision Support Systems: Integrates AI-generated insights into tools that aid human decision-making processes.
3. Collaborative Platforms: Facilitates seamless interaction and collaboration between humans and AI systems.
4. Augmented Reality (AR): Enhances real-world environments with digital information, aiding in tasks that require visual and interactive support.
5. Contextual Computing: Provides relevant and timely information based on the current context, improving the usefulness of AI tools.
6. User Interface (UI) and User Experience (UX) Design: Develops intuitive interfaces that make interacting with AI systems straightforward and effective.

How Do Data Requirements Differ Between Augmented Intelligence and Artificial Intelligence?

Data plays a crucial role in both augmented intelligence and artificial intelligence, but their data requirements differ based on their objectives and functionalities.

Data Requirements for Artificial Intelligence

1. Volume: AI systems often require large volumes of data to learn and make accurate predictions.
2. Variety: Diverse data types, including structured and unstructured data, are necessary for comprehensive analysis.
3. Velocity: High-speed data processing is essential for real-time applications like autonomous driving.
4. Veracity: High-quality, accurate data is crucial to ensure reliable and unbiased AI outcomes.
5. Labeling: In supervised learning, data needs to be labeled accurately for effective training of AI models.

Data Requirements for Augmented Intelligence

1. Relevance: Data used in augmented intelligence systems must be directly relevant to the tasks at hand to provide meaningful insights.
2. Contextuality: Data should include contextual information to help humans interpret AI-generated insights effectively.
3. Accessibility: Data should be easily accessible to users to facilitate seamless interaction with augmented intelligence tools.
4. Accuracy: High-quality data ensures that the insights provided by augmented intelligence systems are reliable and actionable.
5. Integration: Data from various sources should be integrated to provide a comprehensive view that supports human decision-making.

What Are the Security and Privacy Implications of Augmented Intelligence Compared to Artificial Intelligence?

Both augmented intelligence and artificial intelligence entail significant security and privacy considerations, though their implications may differ based on their usage and integration.

Security and Privacy Implications of Artificial Intelligence

1. Data Breaches: AI systems often handle vast amounts of sensitive data, making them targets for cyberattacks.
2. Data Privacy: Ensuring that AI systems comply with data privacy regulations such as GDPR and CCPA is critical.
3. Secure Development Practices: Developing AI systems with robust security measures to prevent unauthorized access and manipulation.
4. Ethical Data Usage: Ensuring that data used by AI systems is obtained and used ethically, respecting user privacy and consent.
5. AI Model Security: Protecting AI models from attacks that attempt to manipulate their outputs or extract sensitive information.

Security and Privacy Implications of Augmented Intelligence

1. Data Protection: Augmented intelligence systems also handle sensitive data that must be protected from breaches and unauthorized access.
2. User Consent: Ensuring that users are aware of and consent to how their data is used by augmented intelligence tools.
3. Access Control: Implementing strict access controls to ensure that only authorized personnel can interact with augmented intelligence systems.
4. Transparency: Providing clear information on how augmented intelligence systems use and protect user data.
5. Continuous Monitoring: Regularly monitoring augmented intelligence systems for potential security vulnerabilities and addressing them promptly.

How Do Augmented Intelligence and Artificial Intelligence Influence Innovation and Creativity Differently?

Both augmented intelligence and artificial intelligence can significantly impact innovation and creativity, but they do so in different ways.

Influence of Artificial Intelligence on Innovation and Creativity

1. Automating Routine Tasks: AI automates repetitive tasks, freeing up time for humans to focus on creative and innovative activities.
2. Generating New Ideas: AI can analyze vast amounts of data to identify patterns and generate new ideas that humans might overlook.
3. Enhancing Research and Development: AI accelerates the research process by quickly analyzing data and simulating experiments.
4. Personalization: AI enables personalized experiences and products, fostering innovation in customer-focused solutions.
5. Creative Collaborations: AI tools can collaborate with humans in creative processes, such as composing music, designing art, or writing content.

Influence of Augmented Intelligence on Innovation and Creativity

1. Enhancing Human Capabilities: Augmented intelligence provides tools that enhance human creativity and problem-solving abilities.
2. Facilitating Collaboration: Augmented intelligence systems enable better collaboration among team members by providing shared insights and information.
3. Supporting Decision-Making: By providing data-driven insights, augmented intelligence helps humans make more informed and creative decisions.
4. Encouraging Experimentation: Augmented intelligence tools can simulate various scenarios, encouraging experimentation and innovative thinking.
5. Enhancing Learning and Development: Augmented intelligence supports continuous learning, allowing individuals to develop new skills and knowledge that fuel creativity.

What Are the Practical Steps to Transition from Artificial Intelligence to Augmented Intelligence in an Organization?

Transitioning from solely utilizing artificial intelligence to incorporating augmented intelligence involves strategic changes in technology, workflow, and organizational culture. Here are practical steps organizations can take:

1. Define Clear Objectives

• Artificial Intelligence: Focus on automating specific tasks and processes.
• Augmented Intelligence: Aim to enhance human decision-making and productivity.

Clearly define what you want to achieve with augmented intelligence, such as improving employee efficiency, enhancing customer experiences, or fostering innovation.

2. Assess Current Capabilities

Evaluate the existing AI systems and identify areas where human collaboration can be enhanced. Determine the strengths and weaknesses of your current AI implementations to understand where augmented intelligence can add value.

3. Invest in User-Centric Tools

Develop or acquire tools that are designed to work alongside humans. These tools should have intuitive interfaces and features that facilitate easy interaction and collaboration between humans and AI systems.

4. Train and Educate Employees

Provide comprehensive training programs to help employees understand how to use augmented intelligence tools effectively. Focus on building skills that complement the technology, such as data interpretation, critical thinking, and collaborative problem-solving.

5. Foster a Collaborative Culture

Encourage a culture that values collaboration between humans and machines. Promote teamwork and open communication to ensure employees feel comfortable working with augmented intelligence systems.

6. Implement Incrementally

Start by integrating augmented intelligence into specific areas or departments before scaling up. Use pilot projects to test the effectiveness of augmented intelligence tools and gather feedback for improvement.

7. Ensure Data Integration and Quality

Ensure that data from various sources is integrated seamlessly and maintains high quality. Reliable data is essential for augmented intelligence systems to provide accurate and meaningful insights.

8. Monitor and Evaluate Performance

Regularly monitor the performance of augmented intelligence systems and assess their impact on human productivity and decision-making. Use feedback to make necessary adjustments and improvements.

9. Promote Ethical Practices

Establish ethical guidelines for using augmented intelligence, ensuring that it enhances human capabilities without compromising privacy, fairness, or transparency.

10. Scale and Expand

Once augmented intelligence systems are successfully implemented in initial areas, gradually expand their application across the organization. Continuously explore new opportunities to enhance human intelligence and productivity through technology.

What Are Common Misconceptions About Augmented Intelligence and Artificial Intelligence?

Understanding the true nature of augmented and artificial intelligence can help address common misconceptions that can hinder their effective implementation.

Common Misconceptions About Artificial Intelligence

1. AI Will Replace All Human Jobs:
   • Reality: AI automates specific tasks but often creates new job opportunities and augments human capabilities rather than completely replacing jobs.
2. AI Can Think and Feel Like Humans:
   • Reality: AI systems can mimic certain aspects of human intelligence but do not possess consciousness, emotions, or true understanding.
3. AI is Inherently Biased:
   • Reality: AI can perpetuate biases present in training data, but with careful design and data management, biases can be minimized.
4. AI Development Requires Superintelligent Machines:
   • Reality: Most AI applications today operate at narrow levels of intelligence, focusing on specific tasks rather than overall human-like intelligence.
5. AI Systems are Completely Autonomous:
   • Reality: Many AI systems require human oversight and intervention, especially in critical decision-making processes.

Common Misconceptions About Augmented Intelligence

1. Augmented Intelligence is Just Another Term for AI:
   • Reality: While related, augmented intelligence specifically refers to AI systems designed to assist and enhance human capabilities, not replace them.
2. Augmented Intelligence Does Not Involve Automation:
   • Reality: Augmented intelligence can include automation of repetitive tasks, but its primary focus is on collaboration between humans and machines.
3. Augmented Intelligence Requires Advanced Technical Skills:
   • Reality: Augmented intelligence tools are designed to be user-friendly, enabling individuals with varying technical skills to benefit from them.
4. Augmented Intelligence Weakens Human Decision-Making:
   • Reality: Augmented intelligence strengthens decision-making by providing additional insights and information, allowing for more informed choices.
5. Augmented Intelligence Eliminates the Need for Human Judgment:
   • Reality: Augmented intelligence relies on human judgment to interpret and act on the insights provided by AI systems.

Frequently Asked Questions (FAQ)

Is Augmented Intelligence the Same as Artificial Intelligence?

No. Augmented intelligence focuses on enhancing human capabilities, while artificial intelligence aims to create autonomous systems that perform tasks independently.

Can Artificial Intelligence Enhance Human Decision-Making?

Yes. AI can provide data-driven insights that aid humans in making more informed and effective decisions.

Does Augmented Intelligence Replace Human Jobs?

No. Augmented intelligence is designed to work alongside humans, enhancing their roles rather than replacing them.

Is Artificial Intelligence More Expensive to Implement Than Augmented Intelligence?

Yes. AI systems often require significant investment in technology and expertise, whereas augmented intelligence focuses on enhancing existing human capabilities with potentially lower implementation costs.

Can Both Artificial Intelligence and Augmented Intelligence Be Used Together?

Yes. These technologies can complement each other, with AI handling complex data processing and augmented intelligence providing tools for human decision-making.

Is training required to use augmented intelligence tools?

Yes. Training is essential to ensure that users can effectively interact with and utilize augmented intelligence systems.

Does Augmented Intelligence Ensure Data Privacy?

Yes. When properly implemented, augmented intelligence systems can include robust data privacy measures to protect user information.

Useful Resources

• Gartner’s Insights on AI and Augmented Intelligence
• Harvard Business Review on Augmented vs. Artificial Intelligence
• MIT Sloan Management Review: Augmented Intelligence
• International Association for Artificial Intelligence (IAAI)
• Institute of Electrical and Electronics Engineers (IEEE) on AI Ethics
• McKinsey & Company’s Reports on AI and Augmented Intelligence

Additional Resources

• Artificial Intelligence: A Modern Approach by Stuart Russell and Peter Norvig
• The Future of Augmented Intelligence by Accenture
• AI and Augmented Intelligence in Business by Deloitte
• Stanford University’s AI Index Report
• World Economic Forum on the Fourth Industrial Revolution
• OpenAI’s Research on Artificial and Augmented Intelligence