• Programming Languages and Algorithms: Proficiency in programming languages such as Python, Java, or R is essential. These languages enable team members to write efficient code, manipulate and analyze data, and implement machine learning algorithms. Understanding algorithms, from classic ones like linear regression to cutting-edge deep learning models, empowers AI professionals to leverage mathematical principles and statistical techniques to train and optimize AI systems.
• Data Analysis and Management: AI relies on data, making data analysis and management skills crucial. AI team members need to be adept at collecting, cleaning, and preprocessing data, ensuring its quality and relevance. They must possess the knowledge of statistical methods, data visualization techniques, and data engineering practices to extract insights from complex datasets and prepare them for AI model training.
• Machine Learning and Neural Networks: Technical skills in machine learning are at the heart of AI systems. Understanding machine learning algorithms, such as decision trees, support vector machines, or convolutional neural networks, enables AI team members to create models that can learn from data and make intelligent predictions or decisions. Expertise in neural networks and deep learning architectures equips professionals with the ability to develop complex models capable of handling tasks like image recognition, natural language processing, and reinforcement learning.
• AI Frameworks and Tools: Proficiency in AI frameworks and tools (such as TensorFlow, Keras, PyTorch, Caffe, Scikit-learn, and others) are essential for building AI systems efficiently. These frameworks provide pre-built modules, libraries, and APIs that simplify the implementation of AI algorithms and models. Technical skills in utilizing these tools effectively enable AI team members to accelerate the development process, streamline model training, and optimize system performance.
• Domain Knowledge and Application-Specific Skills: Technical skills also encompass domain knowledge and application-specific expertise. Understanding the nuances of the industry or problem domain in which AI is being applied allows professionals to tailor AI solutions to meet specific requirements. For example, healthcare-focused AI projects may require knowledge of medical terminologies and regulatory considerations, while AI solutions for financial services may demand expertise in risk assessment and fraud detection.

• Effective Communication and Technical Expertise: Communication bridges the gap between AI professionals and others who may not possess technical backgrounds. AI experts with strong communication skills can articulate complex technical concepts in plain English, ensuring that everyone involved understands the goals, challenges, and progress of the project. By effectively conveying ideas, AI professionals foster collaboration, gather valuable insights, and create a shared vision for AI initiatives.
• Collaboration and Problem-Solving: Collaboration is at the core of AI development, and soft skills such as teamwork, empathy, and active listening facilitate effective collaboration among diverse team members. AI teams with strong collaboration skills can effectively pool their technical expertise, brainstorm ideas, and solve complex problems together. By leveraging their collective intelligence and diverse perspectives, AI teams can overcome challenges, refine AI models, and optimize the performance of AI solutions.
• Critical Thinking and Technical Innovation: Critical thinking, coupled with technical expertise, leads to innovative AI solutions. AI professionals with strong critical thinking skills can evaluate different approaches, challenge assumptions, and identify potential shortcomings or biases in AI models. They can think creatively to address issues such as data biases or fairness concerns, ensuring that AI systems are developed responsibly and ethically.
• Leadership and Team Empowerment: Effective leadership in AI projects involves establishing and maintaining a collaborative and inclusive environment, empowering team members, and harnessing their full potential. AI leaders with exceptional interpersonal abilities can inspire and motivate their team, foster a culture of continuous learning, and provide guidance in navigating complex technical challenges. They encourage interdisciplinary collaboration, respect diverse perspectives, and drive the team towards achieving AI objectives.

• Training Programs and Workshops: Implement specialized training programs and workshops focused on enhancing soft skills. Offer courses in effective communication, leadership (including how to navigate the phases of team development), problem-solving, critical thinking, and collaboration. These programs can provide AI professionals with the necessary tools and techniques to effectively apply soft skills in their work.
• Interdisciplinary Collaboration and Knowledge Sharing: Encourage interdisciplinary collaboration by creating opportunities for AI team members to work alongside experts from diverse fields such as psychology, design, ethics, and business. This collaboration allows for cross-pollination of ideas, encourages different perspectives, and broadens the skill set of AI teams. Foster a culture of knowledge sharing, where professionals can learn from each other and leverage their collective experiences and expertise.
• Real-World Project Engagement: Provide AI team members with opportunities to work on (other) real-world projects, allowing them to apply their soft skills in practical scenarios. Engaging in projects that involve interaction with clients, end-users, and stakeholders helps AI team members develop effective communication, problem-solving, and teamwork skills.
• Continuous Learning and Professional Development: Encourage AI team members to engage in continuous learning and professional development activities. This can include attending conferences, participating in webinars, reading industry publications, and pursuing certifications in relevant areas. Promote a growth mindset among AI team members, emphasizing the importance of lifelong learning and staying current with the latest developments in both technical and soft skills domains.
• Mentorship and Coaching: Establish mentorship and coaching programs where experienced AI professionals guide and support individuals with less experience. Mentors can provide valuable insights, share their experiences, and offer guidance on developing skills. Regular feedback and coaching sessions help AI professionals identify areas for improvement and provide targeted development opportunities.

• Accenture (2023, March 30). Accenture Technology Vision 2023: Generative AI to Usher in a Bold New Future for Business, Merging Physical and Digital Worlds. Available at: https://newsroom.accenture.com/news/accenture-technology-vision-2023-generative-ai-to-usher-in-a-bold-new-future-for-business-merging-physical-and-digital-worlds.htm.
• Alsever, Jennifer (2020, January 20). Medicine by Machine: Is A.I. the Cure for the World’s Ailing Drug Industry? Fortune. Available at: https://fortune.com/longform/ai-artificial-intelligence-medicine-healthcare-pharmaceutical-industry.
• Anthropic (2023, March 14). Introducing Claude. Available at: https://www.anthropic.com/news/introducing-claude.
• Berlin School of Business and Innovation (2022, September 22). How Do Technical Abilities Combined with Leadership Skills Fuel Career Growth? Available at: https://www.berlinsbi.com/blog/career-advice/how-do-technical-abilities-combined-with-leadership-skills-fuel-career-growth.
• Bhatti, Shawaiz, Demir, Mustafa, Cooke, Nancy J., & Johnson, Craig J. (2021). Assessing Communication and Trust in an AI Teammate in a Dynamic Task Environment. In: 2021 IEEE 2nd International Conference on Human-Machine Systems (ICHMS): 1–6. DOI: 10.1109/ICHMS53169.2021.9582626.
• Brooks, David (2023, February 2). In the Age of A.I., Major in Being Human. The New York Times. Available at: https://www.nytimes.com/2023/02/02/opinion/ai-human-education.html.
• C3.ai (n.d.). Best Practices in Prototyping: Cross-Functional Teams. Available at: https://c3.ai/introduction-what-is-machine-learning/cross-functional-teams/.
• Crampton, Natasha (2021, January 19). The Building Blocks of Microsoft’s Responsible AI Program. Microsoft. Available at: https://blogs.microsoft.com/on-the-issues/2021/01/19/microsoft-responsible-ai-program.
• Dolev, Niva, & Itzkovich, Yariv (2020). In the AI Era, Soft Skills are the New Hard Skills. In: Artificial Intelligence and Its Impact on Business, pp. 55-77. Charlotte, NC: Information Age Publishing.
• Dzombak, Rachel, & Palat, Jay (2021, August 30). 5 Ways to Start Growing an AI-Ready Workforce. Pittsburgh, PA: Software Engineering Institute, Carnegie Mellon University.
• Elliott, Joshua (n.d.). Artificial Social Intelligence for Successful Teams (ASIST). Arlington, VA: Defense Advanced Research Projects Agency (DARPA).
• Exceptional Agility (2023, April 10). What's the Future of Agile? Available at: https://exceptionalagility.com/blog/files/the-future.html.
• Fountaine, Tim, McCarthy, Brian, & Saleh, Tamim (2019). Building the AI-Powered Organization. Harvard Business Review, 97 (4): 62–73.
• Gartner (2020, December 15). How to Staff Your AI Team. Available at: https://www.gartner.com/smarterwithgartner/how-to-staff-your-ai-team.
• Gong, Michelle; and Zhernov, Anton (2019, November 18). Advanced Machine Learning Helps Play Store Users Discover Personalised Apps. Google DeepMind. Available at: https://deepmind.google/discover/blog/advanced-machine-learning-helps-play-store-users-discover-personalised-apps/.
• Gorman, Austin (2023, April 27). How to Strengthen Your Soft Skills for AI and the Future of Work. Fast Company. Available at: https://www.fastcompany.com/90887540/how-to-strengthen-your-soft-skills-for-ai-and-the-future-of-work.
• GovExec Events (2020, July 1). Human Machine Team: The Intersection of Diverse Skill Sets [Video]. Defense One. Available at: https://www.youtube.com/watch?v=93wbNLKpbxg&t=1s.
• Graffius, Scott M. (2023, May 1). Fueling the Development of Innovative and Life-Changing AI Solutions [Presentation]. Talk delivered to an audience of Technology professionals (including Data Scientists, Machine Learning Engineers, Data Engineers, AI Researchers, Project Managers, Business Analysts, UX Designers, Software Developers, Cloud Architects, Data Privacy and Security Specialists, and others involved or interested in AI) at a private event in Mountain View, California, United States. Digital Object Identifier (DOI): 10.13140/RG.2.2.27956.73601. DOI link: https://dx.doi.org/10.13140/RG.2.2.27956.73601.

• Graffius, Scott M. (2023, April 26). The Science of High-Performance Teams [Presentation]. Talk delivered at the DevOps Institute’s SKILup Day 2023 Conference. Digital Object Identifier (DOI): 10.13140/RG.2.2.15888.28169. DOI link: https://dx.doi.org/10.13140/RG.2.2.15888.28169.

• Graffius, Scott M. (2023, January 9). Use the Phases of Team Development (Based on Bruce W. Tuckman's Model of Forming, Storming, Norming, Performing, and Adjourning) to Help Teams Grow and Advance: 2023 Update. Available at: https://scottgraffius.com. Digital Object Identifier (DOI): 10.13140/RG.2.2.10720.35846. DOI link: https://dx.doi.org/10.13140/RG.2.2.10720.35846.

• Graffius, Scott M. (2022, May 13). Want Happier and More Productive DevOps Teams? [Presentation]. Talk delivered at DevOpsDays Geneva, Switzerland 2022 Conference. Digital Object Identifier (DOI): 10.13140/RG.2.2.22252.85127. DOI link: https://dx.doi.org/10.13140/RG.2.2.22252.85127.

• Graffius, Scott M. (2021, October 5). Navigate the Phases of Team Development with Speed and Agility for Happier and More Productive Teams [Presentation]. Talk delivered at the Institute of Electrical and Electronics Engineers IEEE Day 2021 Conference. Digital Object Identifier (DOI): 10.13140/RG.2.2.20055.19365. DOI link: https://dx.doi.org/10.13140/RG.2.2.20055.19365.

• Graffius, Scott M. (2021, February 20). But First, the Team! [Presentation]. Talk delivered at the Brno, Czech Republic DevConf.CZ 2021 Conference. Digital Object Identifier (DOI): 10.13140/RG.2.2.29016.72964. DOI link: https://dx.doi.org/10.13140/RG.2.2.29016.72964.
• Gupta, Arun (2022). Non-Technical Skills Eat Technical Skills for Breakfast [Video]. Recording of Arun Gupta, VP and GM of the Open Ecosystem at Intel, speaking at the All Things Open Conference. Available at: https://www.youtube.com/watch?v=WNPxRBhYNU4.
• Humpton, Barbara (n.d.). The Future of Jobs. Siemens. Available at: https://www.siemens.com/us/en/company/press/siemens-stories/ceo-perspective/the-future-of-jobs.html.
• IBM (2019, September 26). Assemble the Team to Support a Data-Driven Project. Available at: https://www.ibm.com/garage/method/practices/culture/assemble-team-for-data-driven-project.
• IBM (2019). Everyday Ethics for Artificial Intelligence. Available at: https://www.ibm.com/watson/assets/duo/pdf/everydayethics.pdf.
• Institute of Electrical and Electronics Engineers (IEEE) (2021, November 8). The IEEE Global Initiative on Ethics of Autonomous and Intelligent Systems. Available at: https://standards.ieee.org/industry-connections/ec/autonomous-systems.html.
• Kenan Institute (2023, February 20). The Must-Have Skills in the Era of Artificial Intelligence: How AI’s Democratization Will Impact Workers. Available at: https://kenaninstitute.unc.edu/commentary/the-must-have-skills-in-the-era-of-artificial-intelligence-how-ais-democratization-will-impact-workers.
• Lindzon, Jared (2017, February 28). How AI is Changing the Way Companies are Organized. Fast Company. Available at: https://www.fastcompany.com/3068492/how-ai-is-changing-the-way-companies-are-organized.
• Marr, Bernard (2023, March 20). Beyond The Hype: What You Really Need to Know About AI In 2023. Forbes. Available at: https://www.forbes.com/sites/bernardmarr/2023/03/20/beyond-the-hype-what-you-really-need-to-know-about-ai-in-2023.
• Massachusetts Institute of Technology (MIT) Lincoln Laboratory (2023, January 17). Human-AI Performance Incubator. Available at: https://www.ll.mit.edu/r-d/projects/human-ai-performance-incubator.
• Massachusetts Institute of Technology (MIT) (2021, January). Cognitive Science as a New People Science for the Future of Work. Available at: https://workofthefuture.mit.edu/wp-content/uploads/2021/01/2021-Research-Brief-Polli-Kassir-Dolphin-Baker-Gabrieli.pdf.
• Massachusetts Institute of Technology (MIT) Sloan (2019, October 15). Winning With AI. MIT Sloan Management Review and Boston Consulting Group. Available at: https://sloanreview.mit.edu/projects/winning-with-ai.
• McNeese, Nathan J., Demir, Mustafa, Chiou, Erin K., & Cooke, Nancy J. (2021). Trust and Team Performance in Human–Autonomy Teaming. International Journal of Electronic Commerce, 25 (1): 51–72. DOI: 10.1080/10864415.2021.1846854.
• Mearian, Lucas (2023, February 24). Skills-Based Hiring Continues to Rise as Degree Requirements Fade. Computerworld. Available at: https://www.computerworld.com/article/3689170/skills-based-hiring-continues-to-rise-as-degree-requirements-fade.html.
• Meta (2017, October 11). Inventing the Future. Available at: https://www.meta.com/blog/quest/inventing-the-future/.
• Microsoft (2019, June 15). Is the Latest Technology the Key to Your Team’s Success, or is There Something Else? Available at: https://devblogs.microsoft.com/premier-developer/is-the-latest-technology-the-key-to-your-teams-success-or-is-there-something-else.
• New South Wales Technical and Further Education Commission (TAFE NSW) (2019). Soft vs. Hard Skills: Why Successful Australian Businesses Need Both. Ultimo, New South Wales: TAFE NSW.
• Nvidia (n.d.). Partner Innovation. Available at: https://www.nvidia.com/en-ph/self-driving-cars/partners/.
• O’Dea, Blathnaid (2023, February 17). These are the Top Skills AI and Analytics Professionals Need. Silicon Republic. Available at: https://www.siliconrepublic.com/advice/top-skills-ai-data-analytics-professionals-need.
• Olmstead, Brett (2023, February 15). Driving AI Success by Engaging a Cross-Functional Team. Available at: https://www.datarobot.com/blog/driving-ai-success-by-engaging-a-cross-functional-team/.
• Organization for Economic Cooperation and Development (OECD) (n.d.). OECD Programme on AI in Work, Innovation, Productivity and Skills. Available at: https://oecd.ai/en/work-innovation-productivity-skills/key-themes/skills.
• Oswald, Andrew. J., Proto, Eugenio, & Sgroi, Daniel (2015). Happiness and Productivity. Journal of Labor Economics, 33 (4): 789-822.
• Project Management Institute (2020, March 10). Tomorrow's Teams Today: The Future of Teaming: Creative, Collaborative and Agile. Pulse of the Profession. Available at: https://www.pmi.org/learning/library/pulse-indepth-tomorrows-teams-today-11941.
• PwC (2017). Sizing the Prize: What’s the Real Value of AI for Your Business and How Can You Capitalise? PwC’s Global Artificial Intelligence Study: Exploiting the AI Revolution. Available at: https://www.pwc.com/gx/en/issues/data-and-analytics/publications/artificial-intelligence-study.html.
• Rayside, Derek (Ed.) (2023, March 29). Software Engineering Capstone Design Project Handbook (2023 Edition). Waterloo, Ontario, Canada: University of Waterloo.
• Romsey, Joseph (2020, November 30). 5 Tips to Help Workers Upskill and Adapt to Artificial Intelligence. Society for Human Resource Management (SHRM). Available at: https://www.shrm.org/resourcesandtools/hr-topics/technology/pages/how-hr-can-help-workers-upskill-and-adapt-to-artificial-intelligence-5-tips.aspx.
• Samsung (2017, May 4). Artificial Intelligence and the Role of Workers. Available at: https://insights.samsung.com/2017/05/04/artificial-intelligence-and-the-role-of-workers/.
• Stanford University (2019, September). Gathering Strength, Gathering Storms. Stanford, CA: Stanford University.
• Tredinnick, Luke (2017). Artificial Intelligence and Professional Roles. Business Information Review, 34 (1): 37–41.
• Ungerleider, Neal (2023, January 1). AI and Jobs: The Human Angle. Available at: https://www.sap.com/denmark/insights/viewpoints/ai-jobs-human-angle.html.
• United Nations Educational, Scientific and Cultural Organization (UNESCO) (2021, July 2). AI Ethics: Another Step Closer to the Adoption of UNESCO’s Recommendation. Available at: https://en.unesco.org/news/ai-ethics-another-step-closer-adoption-unescos-recommendation-0.
• United States Artificial Intelligence Institute (USAII) (2022). Factsheet: Fast-Track Your Artificial Intelligence Career in 2023. Stamford, CT: USAII.
• United States Congress Committee on Science, Space, and Technology (2019, September 24). Artificial Intelligence and the Future of Work. Report for the One Hundred Sixteenth Congress. Available at: https://www.congress.gov/116/chrg/CHRG-116hhrg37740/CHRG-116hhrg37740.pdf.
• University of Leeds (2023, March 2). The Top 5 AI Skills You Need to Land a Job in Artificial Intelligence. Available at: https://pg-online.leeds.ac.uk/blogs/5-skills-needed-for-ai.
• World Manufacturing Foundation (2020). 2020 World Manufacturing Report: Manufacturing in the Age of Artificial Intelligence. Available at: https://worldmanufacturing.org/wp-content/uploads/WorldManufacturingForum2020_Report.pdf.

• Twitter,
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• Implement and use the most popular agile framework―Scrum;
• Deliver products in short cycles with rapid adaptation to change, fast time-to-market, and continuous improvement; and
• Support innovation and drive competitive advantage.

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Tags: #Accenture • #BSBI • #FastCompany • #MIT • #Gartner • #IBM • AI team • #AITeam • AI team skills • #AITeamSkills • Developing and Advancing Soft Skills in AI Teams • The Power of Synergy: Soft Skills and Technical Skills in AI Teams • The Role of Technical Skills in AI Teams • Understanding Soft Skills in AI Teams • United States Artificial Intelligence Institute • Stanford University • Software Engineering Institute • Microsoft • MIT • IEEE • IBM • DARPA • Graffius' work on AI projects • AI teams • AI • Artificial Intelligence • #AIForGood • #MachineIntelligence • #techinnovation • #AISkills • #AISoftSkills • #AIJobs • #ArtificialIntelligenceSkills • #ArtificialIntelligenceTeamSkills • #ArtificialIntelligenceSoftSkills • #AIResearch • #MI • #AIIsATeamSport • #BigData • #Collaboration • #Data • #Development • #DeepLearning • #AgileBlog • #Keras • #TensorFlow • #Caffe • #PyTorch • #ScikitLearn • #BusinessBlog • #TechnologyBlog • #ProjectManagementBlog • #Leadership • #Tech • #Teamwork • #AIStory • #Technology • #Blog • #TechnicalSkills • #TeamLeadership • #TeamDevelopment • #TeamCollaboration • #TeamBuilding • #SoftSkills • #Team • #ProjectManager • #ProjectManagement • #Management • #ML • #MachineLearning • #Innovation • #Future • #Entrepreneurship • #Engineering • #ChangeManagement • #ArtificialIntelligence • #AIteams • #AI • #Agile • #PwC • #Startups • #Science • #NeuralNetworks • #Programming • #AITradecraft • #autonomousSystems • #USAII • #FutureOfWork • #DataScience • #CognitiveComputing • #emergingtech • #IEEE • #Microsoft • #CoreSkills • #Interpersonalskills • #PeopleSkills • #transferableskills • #transversalskills • #PowerSkills • AI Skills • AI teams • AI Soft Skills • AI Hard Skills • AI team skills • AI technical skills • AI interpersonal skills

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• Implement and use the most popular agile framework―Scrum;
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1. AI Research Scientist: AI research scientists are responsible for conducting research and developing cutting-edge AI algorithms and models.
2. AI Software Engineer: AI software engineers are responsible for integrating AI components into software applications. They bridge the gap between AI research and practical implementation, making AI systems usable by end-users.
3. Data Engineer: Data engineers are responsible for building and managing the data pipelines that feed AI models. They ensure that data is collected, cleaned, and prepared in a format suitable for analysis and model training.
4. Data Scientist: Data scientists are experts in data analysis and interpretation. They preprocess, analyze, and extract valuable insights from data, which is vital for training and improving AI models.
5. Machine Learning Engineer: Machine learning engineers focus on implementing and deploying machine learning models into practical applications. They work to ensure that AI models are integrated into software systems effectively.

1. AI DevOps Engineer: Combines development and operations skills to streamline AI model deployment. They automate tasks.
2. AI Ethicist: Ensures that AI systems are developed and used responsibly and ethically.
3. AI Infrastructure Engineer: Builds and maintains the infrastructure required for AI model deployment and scalability.
4. AI Legal and Compliance Specialist: Ensures AI projects comply with legal and regulatory requirements.
5. AI Marketing Specialist: Promotes and markets AI products and solutions to customers and stakeholders.
6. AI Operations (AIOps) Specialist: Focuses on the operational aspects of AI, including monitoring, maintenance, and troubleshooting.
7. AI Product Manager: Oversees the development and deployment of AI products.
8. AI Project Manager: Leverages general and specialized hard skills and soft skills, and applies their understanding of many aspects of artificial intelligence (such as machine learning, deep learning, automation, robotics, and natural language processing) to manage the planning, execution, and delivery of AI projects. Note: Titles vary by organization; the position may be called an AI Project Manager, AI Program Manager, Agile Project Manager, Technical Project Manager, Scrum Master, or another related designation.
9. AI QA Engineer: Ensures the quality and reliability of AI models through testing and validation.
10. AI Research Scientist: Conducts research to develop new AI algorithms and models.
11. AI Software Engineer: Builds and maintains software systems that incorporate AI components.
12. AI Trainer/Annotator: Prepares and labels data for training AI models, especially for supervised learning.
13. AI UX/UI Designer: Designs user interfaces and experiences for AI-powered applications.
14. Computer Vision Engineer: Specializes in developing AI models for image and video analysis.
15. Data Analyst: Examines data to uncover trends and insights that can guide AI projects.
16. Data Engineer: Manages data pipelines and prepares data for analysis and model training.
17. Data Scientist: Analyzes and interprets data to extract insights and inform AI models.
18. Deep Learning Engineer: Focuses on deep neural networks and architectures.
19. Machine Learning Engineer: Focuses on implementing and deploying machine learning models.
20. Natural Language Processing (NLP) Engineer: Specializes in working with text and language-related AI tasks.

• Apple (n.d.). Careers at Apple: Machine Learning and AI. Available at: https://www.apple.com/careers/us/machine-learning-and-ai.html.
• C3.ai (n.d.). Best Practices in Prototyping: Cross-Functional Teams. Available at: https://c3.ai/introduction-what-is-machine-learning/cross-functional-teams/.
• Deloitte AI Institute (2021). Building Successful AI Teams. Available at: https://www2.deloitte.com/content/dam/Deloitte/us/Documents/deloitte-analytics/us-ai-institute-building-successful-AI-teams.pdf.
• Gartner (2020, December 15). Staff AI Teams with Various Roles and Skills for Success. Available at: https://www.gartner.com/smarterwithgartner/how-to-staff-your-ai-team.
• General Services Administration (GSA) Centers of Excellence (CoE) (n.d.). AI Guide for Government. Available at: https://coe.gsa.gov/coe/ai-guide-for-government/understanding-ai-job-roles-career-path/.
• Google Quantum AI (n.d.). Careers. Available at: https://quantumai.google/team/careers.
• Graffius, Scott M. (2023, May 1). AI is a Team Sport: A Confluence of Diverse Technical and Soft Skills are Crucial for Success. Available at: https://www.scottgraffius.com/blog/files/successful-ai-teams.html.
• Graffius, Scott M. (2023). What Successful AI Teams Have in Common [Video]. Graffius’ talk at the 2023 Conf42 Quantum Computer Conference. Available at: https://www.youtube.com/watch?v=u2qRKFbSKYE.
• IBM (n.d.). Assemble the Team to Support a Data-Driven Project. Available at: https://www.ibm.com/garage/method/practices/culture/assemble-team-for-data-driven-project/.
• Intel (n.d.). Artificial Intelligence Teams: Careers. Available at: https://jobs.intel.com/en/search-jobs/artificial+intelligence/599/1.
• Intuit (2020, December 8). How to avoid conflicts and delays in the AI development process (Part I). Available at: https://blogs.intuit.com/2020/12/08/how-to-avoid-conflicts-and-delays-in-the-ai-development-process-part-i/.

• Twitter,
• Facebook, and
• LinkedIn.

• Implement and use the most popular agile framework―Scrum;
• Deliver products in short cycles with rapid adaptation to change, fast time-to-market, and continuous improvement; and
• Support innovation and drive competitive advantage.

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• Twitter,
• Facebook, and
• LinkedIn.

• Implement and use the most popular agile framework―Scrum;
• Deliver products in short cycles with rapid adaptation to change, fast time-to-market, and continuous improvement; and
• Support innovation and drive competitive advantage.

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• 🇦🇹 Austria
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• Facebook,
• Instagram,
• LinkedIn,
• Pinterest,
• Snapchat,
• TikTok,
• X (formerly Twitter),
• and YouTube.

• From Simple to Complex (the genesis of social media algorithms),
• General Mechanics (the components of algorithms),
• Benefits and Risks (the upside and downside of algorithms),
• Algorithm-Savvy Marketing,
• Ethical Considerations,
• The Future of Algorithms on Social Media Platforms, and
• Conclusion

1. User Engagement: Engagement is at the heart of algorithms. The more users interact with specific content, the more likely it is to be promoted within feeds. This initiates a cycle where popular content gains even more prominence.

2. Content Prioritization: Here are examples of how different social media platforms treat content. The terms “advances,” “favors,” and “prioritizes” are used interchangeably.

• Facebook advances live videos.
• Instagram favors images and videos.
• LinkedIn prioritizes thought leadership posts.
• Pinterest advances pins about recipes, home décor, and fashion; and pins that link to external websites such as blogs.
• Snapchat prioritizes content that uses filters and lenses.
• TikTok advances videos that receive high engagement rates within seconds of being posted.
• X increasingly favors videos.
• YouTube prioritizes long videos with high watch times.

3. Content Relevance: Algorithms prioritize content that aligns with users’ preferences and history. For example, if a user frequently engages with fitness-related posts, the algorithm will likely serve them with similar content. That tactic can enhance user satisfaction, but it can also lead to echo chambers. Those are environments that expose users primarily to information that reinforces their existing beliefs.

4. Freshness: Social media thrives on immediacy. Newer content often takes precedence over older posts. That compels brands, influencers, and others to maintain an apt posting schedule.

5. Network Effects: Content gaining traction among a user’s network helps amplify its reach by spreading (more) rapidly, including possibly ‘going viral.’ There is no universal quantification for what constitutes ‘viral,’ but a post with 1 million or more views/impressions may qualify.

1. Personalization: Individuals tend to interact more frequently with content that aligns with their preferences.

2. Content Discovery: Algorithms can facilitate the introduction of content and accounts that users may not have encountered otherwise.

3. Reduced Information Overload: Social media platforms house a massive volume of content. Algorithms may help filter out the noise. By prioritizing relevant posts, algorithms can help individuals to focus on what matters most to them.

4. Enhanced Engagement: As users find more of the content they enjoy, they will likely spend more time on the platform. This increased engagement also benefits platforms as they can monetize the increased time and attention through advertising.

1. Echo Chambers and Polarization: The potential formation of echo chambers is the most concerning byproduct of algorithmic personalization. Users are at risk of being shielded from differing perspectives. That is especially the case with political discourse; those situations can lead to polarization or increased polarization.

2. Risk of Promoting Incorrect Information: The algorithms that prioritize engagement can potentially (by design or inadvertently) boost sensationalist content or incorrect information.

3. User Fatigue: Users may experience fatigue or disillusionment when they become aware of the potential negative effects of algorithms. Users who feel that their experiences are being engineered may lose trust in the platforms, and they may stop using them.

1. Prioritize Quality Over Quantity: Create meaningful, engaging, and relevant posts.

2. Engage Authentically: Engage with one’s audience in genuine ways such as through storytelling, user-generated content, and responsive interactions.

3. Embrace Video Content: Use videos as platforms are increasingly prioritizing that content.

4. Stay Informed: Marketers should be on the lookout for changes and be responsive to them.

5. Leverage Data Analytics: Informed by metrics, marketers can adjust their strategies when needed.

6. Experiment and Adapt: Platforms are continuously changing. Users’ tastes may change as well. Marketers should experiment with different content types, posting schedules, and engagement tactics to discover what works best for their audience.

1. Transparency: Users deserve to understand how their data is used and how content is prioritized. Increased transparency can foster trust between users and platforms. Is the social media platform transparent about how its algorithm works.

2. Algorithmic Bias: Algorithms are not immune to bias as they often reflect the prejudices in the data they analyze. Is the social media platform taking steps to remove bias wherever possible?

3. Content Moderation: What role, if any, should platforms play in moderating content?

4. User Well-Being: Is the platform primarily focused on providing a great user experience? Or is it about doing anything and everything possible to generate time on the platform and obtain a presumed corresponding increase in revenue?

1. Increased Use of AI and ML: AI and ML will continue to play a role in refining algorithms. As the technologies advance, algorithms will become even more adept at understanding user preferences and predicting behavior.

2. Greater Focus on User Control: Users are becoming more aware of their data and how it’s used. Platforms may offer control to users, allowing users to customize their feeds and manage their engagement preferences.

3. Ethical Algorithm Design: Ethical frameworks that prioritize user well-being, transparency, and accountability may gain prominence in the future.

4. Integration of AR and VR: Social media platforms may incorporate augmented reality (AR) and virtual reality (VR) elements into their algorithms in the future. If that happens, the result will be immersive user experiences that transcend traditional content consumption.

5. Community-Centric Algorithms: Algorithms in the future may prioritize community engagement and collective interests.

1. Adobe (2023, September 8). Guide to Beating Social Media Algorithms. Available at: https://creativecloud.adobe.com/learn/express/web/increase-social-media-visibility.
2. Alalwan, A. A. (2018). Investigating the Impact of Social Media Advertising Features on Customer Purchase Intention. International Journal of Information Management, 42: 65–77. DOI: https://doi.org/10.1016/j.ijinfomgt.2018.06.001.
3. Allen, R., & Choudhury, P. (2022). Algorithm-Augmented Work and Domain Experience: The Countervailing Forces of Ability and Aversion. Organization Science, 33 (1): 149-169.
4. Ananny, M. (2016). Toward an Ethics of Algorithms: Convening, Observation, Probability, and Timeliness. Science, Technology, and Human Values, 41(1): 93-117. DOI: https://doi.org/10.1177/0162243915606523.
5. Bensley, Robert J., & Brookins-Fisher, Jodi (2023, December 14). Community and Public Health Education Methods: A Practical Guide—Fifth Edition. Burlington, MA: Jones & Bartlett Learning.
6. Berberich, N., Nishida, T., & Suzuki, S. (2020). Harmonizing Artificial Intelligence for Social Good. Philosophy and Technology, 33: 613-638.
7. Berkessel, Juergen (2021, October 27). How Evergreen Posting on Social Media for Podcasters Creates Growth. Season 1, Episode 9 of the Podcasting Strategy Show. Available at: https://polymash.com/evergreen-posting.
8. Burton, Taylor (2022, November 2). Social Media Marketing: Leveraging LinkedIn. Pennsylvania Bar Institute. Available at: https://go.pbi.org/blog/social-media-marketing-leveraging-linkedin.
9. Center for Direct Marketing (2022, September 27). What Is the Average Lifespan of a Blog or Social Media Post? Available at: https://dmcenter.com/lifespan-of-a-post.
10. Cleland, C.E. (2001). Recipes, Algorithms, Programs. Minds and Machines, 11: 219-237.
11. Colicev, Anatoli, & Malshe, Ashwin, & Pauwels, Koen, & O'Connor, Peter (2018). Improving Consumer Mindset Metrics and Shareholder Value Through Social Media: The Different Roles of Owned and Earned Media. Journal of Marketing, 82 (1): 37-56.
12. Confederation of European Waste-to-Energy Plants (CEWEP) (2023, June 15). The Power of Social Media and How to Use It. 10th CEWEP Waste-to-Energy Congress, 14th - 16th June 2023, Berlin. Available at: https://www.cewep.eu/congress2023presentations/ and https://www.cewep.eu/wp-content/uploads/2023/06/4.1-Monika-Michalska.pdf.
13. Degraux, Xavier (2022, November 5). Quelle est la Durée d’un Post sur Twitter, Instagram, LinkedIn. Available at: https://www.xavierdegraux.be/quelle-est-la-duree-dun-post-sur-twitter-instagram-linkedin.
14. Encompass Online Marketing (2023, March 15). How Often Should You Publish New Content? Available at: https://encompassonline.ca/blog/how-often-should-you-publish-new-content.
15. Expand My Business (2024, January 11). How to Leverage User Experience: UX in Digital Marketing. Available at: https://blog.emb.global/ux-in-digital-marketing/.
16. Frau-Meigs, Divina.(2024, June). Algorithm Literacy as a Subset of Media and Information Literacy: Competences and Design Considerations. Digital, 4: 512-528. DOI: 10.3390/digital4020026.
17. Graffius, Scott M. (2023, May 1). Fueling the Development of Innovative and Life-Changing AI Solutions [Presentation]. Talk delivered to an audience of Technology professionals (including Data Scientists, Machine Learning Engineers, Data Engineers, AI Researchers, Project Managers, Business Analysts, UX Designers, Software Developers, Cloud Architects, Data Privacy and Security Specialists, and others involved or interested in AI) at a private event in Mountain View, California, United States. Digital Object Identifier (DOI): 10.13140/RG.2.2.27956.73601. DOI link: https://dx.doi.org/10.13140/RG.2.2.27956.73601.
18. Graffius, Scott M. (2024, January 1). Lifespan (Half-Life) of Social Media Posts: Update for 2024. Available at: https://scottgraffius.com/blog/files/social-24.html. DOI: 10.13140/RG.2.2.21043.60965.
19. Grandinetti, J. (2021). Examining embedded apparatuses of AI in Facebook and TikTok. AI and Society, 38: 1273-1286. DOI: https://doi.org/10.1007/s00146-021-01270-5.
20. Hill, R.K. (2013). What an Algorithm Is, and Is Not. Communications of the ACM, 56 (6): 8-9. DOI: 10.1145/2461256.2461260.
21. IBM (n.d.). What Is Social Media Analytics. Available at: https://www.ibm.com/topics/social-media-analytics.
22. John, Vanessa (2024, September 5). Website vs. Social Media - Do You Still Need a Site in 2024? Madgicx. Available at: https://madgicx.com/blog/website-and-social-media.
23. Jwaniat, M. A. (2023). Examining Journalistic Practices in Online Newspapers in the Era of Artificial Intelligence. 2023 International Conference on Intelligent Computing, Communication, Networking and Services (ICCNS), Valencia, Spain, 2023, pp. 183-189, DOI: 10.1109/ICCNS58795.2023.10193607.
24. Keller, J., Herrmann-Schwarz, T., Roitzheim, C., Mertens, L., Christin Brockmeier, L., & Kumar Purohit, A. (2024). A Digital Nudge-Based Intervention to Interrupt Instagram Usage: Randomized Controlled Pilot Study. European Journal of Health Psychology. DOI: https://dx.doi.org/10.1027/2512-8442/a000150.
25. Lang, Kirsti (2023, November 6). Decoding the Facebook Algorithm in 2024: Everything You Need to Know. Available at: https://buffer.com/library/facebook-news-feed-algorithm/.
26. Lin, Yunduan, & Wang, Mengxin, & Zhang, Heng, & Zhang, Renyu, & Shen, Zuo-Jun Max (2021, June 9; revised 2023, June 28). Content Promotion for Online Content Platforms with the Diffusion Effect. SSRN. Available at: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3863104 and https://dx.doi.org/10.2139/ssrn.3863104.
27. Mahesh, B. (2020). Machine Learning Algorithms—A Review. International Journal of Science and Research (IJSR), 9 (1): 381-386. https://doi.org/10.21275/art20203995.
28. Metzler, H., & Garcia, D. (2024). Social Drivers and Algorithmic Mechanisms on Digital Media. Perspectives on Psychological Science, 19 (5): 735-748. DOI: https://doi.org/10.1177/17456916231185057.
29. Mosseri, Adam (2023, May 31). Instagram Ranking Explained. Available at: https://about.instagram.com/blog/announcements/instagram-ranking-explained/.
30. Mosseri, Adam (2021, June 8). Shedding More Light on How Instagram Works. Available at: https://about.instagram.com/blog/announcements/shedding-more-light-on-how-instagram-works.
31. Newberry, Christina (2023, October 25). How Does the LinkedIn Algorithm Work? [2024 Changes Explained]. Available at: https://blog.hootsuite.com/how-the-linkedin-algorithm-works-hacks/.
32. Oladipo, Tamilore (2024, January 11). A 2024 Guide to the YouTube Algorithm: Everything You Need to Know to Boost Your Content. Available at: https://buffer.com/resources/youtube-algorithm/.
33. Perreault, Marie-Catherine, & Mosconi, Elaine (2018). Social Media Engagement: Content Strategy and Metrics Research Opportunities. Proceedings of the 51st Hawaii International Conference on System Sciences: 3568-3577.
34. Pinterest (2023, February 22). A More Positive Internet? It’s Possible. Available at: https://business.pinterest.com/blog/a-better-internet-is-possible/.
35. Pugalia, Akash, & Lalani, Farah (2023, September 29). Digital Safety: How a Multi-Faceted Approach Can Help Tackle Real-World Harm. World Economic Forum. Available at: https://www.weforum.org/agenda/2023/09/digital-safety-multi-faceted-approach-tackle-real-world-harm.
36. Rainey, Clint (2023, August 15). Social Media’s Toxic Impact Can Last Up to 8 Days. This Behavioral Scientist’s Solution Might Surprise You. Available at: https://www.fastcompany.com/90939081/social-media-toxic-impact-content-moderation-solution-behavior-science.
37. Roberts, J. A., & David, M. E. (2020). The Social Media Party: Fear of Missing Out (FOMO), Social Media Intensity, Connection, and Well-Being. International Journal of Human-Computer Interaction, 36 (4): 386-392.
38. Rynek Pro (2023, June 26). Długość Życia Postów (Half-Life) w Mediach Społecznościowych w 2023 Roku. Available at: https://rynek.pro/half-life-dlugosc-zycia-postow/#pll_switcher.
39. Schaffer, Neal (2024). Maximizing LinkedIn for Business Growth: A Practical Guide to Building Your Brand and Driving Results. Irvine, California: PDCA Social.
40. Schneider, Philipp J., & Rizoiu, Marian-Andrei (2023, August 22). The Effectiveness of Moderating Harmful Online Content. Proceedings of the National Academy of Sciences of the United States of America, 120 (34): e2307360120. Available at: https://www.pnas.org/doi/abs/10.1073/pnas.2307360120. DOI: 10.1073/pnas.2307360120.
41. Snapchat (n.d.). How We Rank Content on Spotlight. Available at: https://help.snapchat.com/hc/en-us/articles/8961653169940--How-We-Rank-Content-on-Spotlight.
42. Statista (2024, August 19). Number of Internet and Social Media Users Worldwide as of July 2024. Available at: https://www.statista.com/statistics/617136/digital-population-worldwide/.
43. Stokel-Walker, Chris (2024, March 21). TikTok’s Algorithm has Always Been a Black Box. But Researchers are Finally Figuring It Out. Fast Company. Available at: https://www.fastcompany.com/91065874/researchers-are-finally-figuring-out-how-tiktoks-algorithm-works.
44. Tropp, J., & Baetzgen, A. (2019). Users’ Definition of Snapchat Usage. Implications for Marketing on Snapchat. International Journal on Media Management, 21 (2): 130-156. DOI: https://doi.org/10.1080/14241277.2019.1637343.
45. X.com (2023, March 31). Twitter's Recommendation Algorithm. Available at: https://blog.x.com/engineering/en_us/topics/open-source/2023/twitter-recommendation-algorithm.
46. Yunduan Lin, Mengxin Wang, Heng Zhang, Renyu Zhang, Zuo-Jun Max Shen (2024). Content Promotion for Online Content Platforms with the Diffusion Effect. Manufacturing and Service Operations Management, 26 (3):1062-1081. DOI: https://doi.org/10.1287/msom.2022.0172.
47. Zhao, Junqi, & Li, Peiyuan. (2024, July). Randomized Algorithm: An Advanced Algorithm for Modern Video Games. Theoretical and Natural Science, 43: 168-183. DOI: 10.54254/2753-8818/43/20240856.
48. Zuckerberg, M. (2021). Hearing Before the United States House of Representatives Committee on Energy and Commerce Subcommittees on Consumer Protection & Commerce and Communications & Technology: Testimony of Mark Zuckerberg. Available at: https://docs.house.gov/meetings/IF/IF16/20210325/111407/HHRG-117-IF16-Wstate-ZuckerbergM-20210325-U1.pdf.

• Implement and use the most popular agile framework―Scrum;
• Deliver products in short cycles with rapid adaptation to change, fast time-to-market, and continuous improvement; and
• Support innovation and drive competitive advantage.

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