ORGANIZATIONS

CONTACT

AI Innovation

I’m an…

Strategist

PERSONAL STATEMENT

I’m an AI innovation strategist who is in charge of turning AI technologies into accessible and smart solutions, either hardware, software, or service.

By utilizing my design and research skills, I can produce offerings that are not only technically feasible but also desirable for end users. By using my knowledge of the business model and business case, I can make sure the offerings are viable and profitable.

CHALLENGES

1/3

AI Ethics and

Responsibility

Establishing ethical AI (Jobin et al., 2019) frameworks is crucial to ensure fairness and prevent biases in algorithmic decision-making, maintaining accountability across diverse user groups.

Technical

Transparency

2/3

Google AI…Why?

Step 2 .

I plan to integrate diverse perspectives and expertise, fostering a collaborative environment. My goal is to guide the team through a co-creative process that harnesses both data-driven insights and instinctive knowledge.

AI Sustainability

Advancing AI's explainability (Shin, 2021) is essential to foster trust and understanding, allowing users to comprehend and challenge AI-driven decisions effectively.

Proactive

Holistic

Preparing

It is important to do strategic framing before kick-off, especially when it is a technically complex topic like AI. Therefore, I would try my best to understand the essential theory and mechanism behind AI.

MY CAPABILITIES

Co-creating

I'm drawn to Google’s culture of innovation and its open-source contributions Being a part of Google AI would offer me a chance to work on projects that redefine how we interact with technology.

3/3

Prioritizing sustainable AI (van Wynsberghe, 2021) development is vital for minimizing environmental impact and resource depletion, ensuring the longevity and ethical stewardship of AI technology.

As an AI Innovation Strategist, I aspire to contribute to Microsoft's vision of democratizing AI, enhancing human capabilities, and making advanced AI tools accessible across various platforms.

Microsoft Copilot…Why?

  • Significant growth is expected in both AI software and hardware sectors, with North America leading the market share. (Alekseeva et al., 2021)

  • AI is no longer only applied in daily software like ChatGPT but is applied in more scenarios, such as automotive, banking, and healthcare. (Zhang et al., 2018)

  • As AI technology develops, consumers are getting to know more about it and they’re getting used to it, with an increasingly higher acceptance. (Pelau et al., 2021)

Company :

Affirmative

Participative

Responsive

Systematic

Specific

(Quint et al., 2022)

  • Team mapping (Margerison & McCann, 1984) as a design skill is a strategic approach to understanding and utilizing the strengths of a team effectively. It corresponds to my affirmative leadership by fostering a positive work environment where each member's contributions are recognized and valued. This method involves creating a visual representation of team roles, responsibilities, and relationships, encouraging transparency and affirming the importance of every team member's role in achieving the group’s goals.

  • Co-creation (Sanders & Stappers, 2008) in design aligns with my participative leadership, emphasizing collaboration and shared decision-making. This method involves engaging various stakeholders, including users, in the design process to harness collective creativity and insights. It ensures that the outcomes are widely accepted and valued by incorporating diverse perspectives, fostering a sense of ownership and collective investment in the project’s success.

  • Design road mapping (Simonse et al., 2014) is a planning technique that helps envision the future path of a product or service offering, identifying key milestones and deliverables. It suits both my proactive and intuitive leadership styles, as it requires anticipation of future trends and the strategic direction of innovation. This forward-looking approach ensures that a team is not only reacting to the present but is also actively preparing for future opportunities and challenges.

  • The Value Proposition Canvas (Pokorná et al., 2015) is a tool that enables a designer to align a product’s offerings with the customer's needs, desires, and pain points. It complements holistic leadership by considering the entire ecosystem of the user experience. This method encourages me to think broadly about the customer journey and how each aspect of the business can deliver value, ensuring that solutions are developed with a comprehensive understanding of client needs. It also helps me make holistic decisions concerning the bigger picture.

Embedding

Step 3 .

(Calabretta et al., 2016)

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With a proactive stance, I will set up mechanisms to assess our progress and iterate our approach as needed, leveraging both my intuitive and proactive traits to refine and adjust our strategy for maximum effectiveness.

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Understanding the core strength of the company (of both intellectual properties and people) aligns with my participative type of leadership. This helps me make more holistic and optimized decisions.

I intend to intertwine the company's core competencies and values with emerging AI opportunities, ensuring that our strategic design efforts propel the company forward in a unified and purposeful direction.

To co-change the company, I will champion initiatives that align with our long-term objectives, ensuring that our design outcomes are not just implemented but are also instrumental in shaping the company's evolving strategic direction.

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Mobilizing stakeholders is key in laying the foundation for any strategic initiative. I would actively engage and empower team members and stakeholders, ensuring their insights and needs are heard and addressed from the outset.

My participative leadership ensures that all team members are co-authors of the outcome. This method promotes ownership and encourages diverse contributions, fostering an environment where everyone is motivated to bring their best ideas forward.

With affirmative and holistic leadership, I will cultivate a group of advocates within the team who are deeply connected to the project's goals and can inspire and influence wider adoption and enthusiasm across the organization.

IBM's commitment to ethical AI and ongoing research in areas like natural language processing and machine learning offers an unparalleled environment to contribute to cutting-edge AI solutions.

IBM AI Team…Why?

TRENDS

MY LEADERSHIP

MY 3-STEP MODEL

Project :

People :

Transformative

Step 1 .

Directive

Intuitive

Alekseeva, L., Azar, J., Giné, M., Samila, S., & Taska, B. (2021). The demand for AI skills in the labor market. Labour Economics, 71(0927-5371), 102002. https://doi.org/10.1016/j.labeco.2021.102002

Calabretta, G., Gemser, G., & Karpen, I. (2016). Strategic design : eight essential practices every strategic designer must master. Bis Publishers.

Jobin, A., Ienca, M., & Vayena, E. (2019). The global landscape of AI ethics guidelines. Nature Machine Intelligence, 1(9), 389–399. https://www.nature.com/articles/s42256-019-0088-2

Margerison, C., & McCann, D. (1984). Team Mapping: A New Approach to Managerial Leadership. Journal of European Industrial Training, 8(1), 12–16. https://doi.org/10.1108/eb002166

Pelau, C., Dabija, D.-C., & Ene, I. (2021). What makes an AI device human-like? The role of interaction quality, empathy and perceived psychological anthropomorphic characteristics in the acceptance of artificial intelligence in the service industry. Computers in Human Behavior, 122, 106855. https://doi.org/10.1016/j.chb.2021.106855

Pokorná, J., Pilař, L., Balcarová, T., & Sergeeva, I. (2015). Value Proposition Canvas: Identification of Pains, Gains and Customer Jobs at Farmers’ Markets. Agris On-Line Papers in Economics and Informatics, 7(4), 123–130. https://doi.org/10.7160/aol.2015.070412

Quint, E., Gemser, G., & Calabretta, G. (2022). Design leadership ignited : elevating design at scale. Stanford Business Books, An Imprint Of Stanford University Press.

Sanders, E. B.-N. ., & Stappers, P. J. (2008). Co-creation and the new landscapes of design. CoDesign, 4(1), 5–18. https://doi.org/10.1080/15710880701875068

Shin, D. (2021). The effects of explainability and causability on perception, trust, and acceptance: Implications for explainable AI. International Journal of Human-Computer Studies, 146, 102551. https://doi.org/10.1016/j.ijhcs.2020.102551

Simonse, L. W. L., Hultink, E. J., & Buijs, J. A. (2014). Innovation Roadmapping: Building Concepts from Practitioners’ Insights. Journal of Product Innovation Management, 32(6), 904–924. https://doi.org/10.1111/jpim.12208

van Wynsberghe, A. (2021). Sustainable AI: AI for Sustainability and the Sustainability of AI. AI and Ethics, 1(1). https://doi.org/10.1007/s43681-021-00043-6

Zhang, X., Ming, X., Liu, Z., Yin, D., Chen, Z., & Chang, Y. (2018). A reference framework and overall planning of industrial artificial intelligence (I-AI) for new application scenarios. The International Journal of Advanced Manufacturing Technology, 101(9-12), 2367–2389. https://doi.org/10.1007/s00170-018-3106-3

REFERENCE