Human + Machine
How to apply responsible AI to your business in this innovation economy.
Artificial Intelligence is no longer just a futuristic notion, it’s here right now, leading the 4th Industrial Revolution. And everyone is talking about AI, all the time.
We are all well aware of AI challenges 1. Data management in corporations, 2. Lack of deeply skilled AI talent, 3. Responsible AI needs (moral use, bias or security). But I find there are so many articles online about AI industry disruption that drive too much concern about malicious use of AI or even job loss paranoia.
I recently read “Human + Machine: Reimagining Work in the Age of AI” by Paul R. Daugherty and H. James Wilson, both Accenture leaders, and found their approach to machines and human collaboration and the implications in terms of human resources and new business models, refreshing and inspiring.
AI is not replacing you, it’s empowering you.
CEOs are increasingly aware that jobs of the future in the AI era are in the missing middle and cannot be implemented in silos across modern companies. This is how the authors describe machine and human collaboration:
a) Middle-left side: People developing and deploying AI
1. Trainers: Educating AI on right values and how they should perform, helping natural-language processors and language translators make fewer errors and teaching AI algorithms how to mimic human behaviors. At the end of the day, AI system will only be as good as the data they are trained on.
2. Explainers: Bridging the gap between technologists and business leaders so “black-box” nature of sophisticated ML become transparent and easy, translating the inner workings of complex algorithms into actionable business insights to nontechnical professionals.
3. Sustainers: Applying critical thought to AI and ensuring data quality where necessary for sustainability and stakeholder value. Sustainable AI implies necessarily explainability, accountability, fairness and symmetry.
b) Middle-right side: Machines and AI giving super powers to People
1.Amplification: Where a machine amplifies intelligence to big data for a professional, a team or low-level activity so humans can focus on highest value work and augmenting strategic decisions.
2. Interaction: Where machines and AI agents employ advanced interfaces such as voice-driven natural-language processing.
3. Embodiment: In which AI agents work in combination with sensors, motors and actuators that enable robots to share workspace with humans and engage in physically collaborative work.
AI is already increasing productivity and creating new business models.
Organizations are already looking into how to transform their business, reimagining processes mindful of these new middle jobs needed.
In the journey to apply AI, the authors suggest to find where the business challenges or needs lie. Some industries like communications businesses start from front office (sales and CS), some like financial services start from back office (processes). Large banks are already using AI and ML in their back office processes to flip productivity ratio.
An example of new business model is PitchFix, an online fashion service that is disrupting the retailing industry. It uses proprietary AI that learns from users’ interests on Pinterest so crowdsourced expert stylists can recommend personalized clothing options for specific consumer needs.
“The unprecedented power of AI to transform businesses is creating an urgent and growing challenge,” Wilson said. “To help leaders reimagine their processes and get the most benefit from AI’s power to augment human capability, we developed what we call the ‘MELDS’ framework, with five crucial principles required to become an AI-fueled business: Mindset, Enterprise, Leadership, Data and Skills. Innovative companies can leverage this framework to ride the third wave and capitalize on AI-powered human-machine collaborations.”
Bottom line — This book is full of insights and a great guidance for business leaders on how to apply responsible AI to their business in this innovation economy, adding value and transparency in their exchange with users.
Absolutely recommend having it and sharing it!
Jan 2018. WIRED UK. Interviews Paul Daugherty, author of Human+Machine: Reimagining work in the age of AI.
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