With every place we go and every action we take, it feels like we’re constantly being asked to submit personal data. Download a free app, and you’re asked for your email address. To redeem that discount offer at the pet store, you must supply your phone number. Play a video game, and it wants to connect to your social media.
AI, the artificial intelligence displayed by machines, can be misunderstood if we define it only by what’s seen in media and entertainment – the cute droid sidekicks from a blockbuster movie or the facial-recognition software used by television detectives. AI is really much more, or much less (depending on how you look at these representations).
For this next post in a series exclusive to Data Makes Possible, Dr. Kirk Borne, Principal Data Scientist for Booz Allen Hamilton, explains the real power of AI while discussing its specific application in consumer marketing. How does AI augment and assist those in that business field to take data-driven actions? Will AI replace the human touch?
The growing role of AI in the future of marketing
The massive data collections being accumulated by nearly every industry and organization have a raison d’être: to fuel powerful machine learning algorithms and to enable game-changing AI (artificial / augmented / assisted intelligence). This is perhaps most visibly apparent to us as consumers of products and services.
The providers of goods and services use data, machine learning, and AI to understand us and to get our attention in the crowded noisy marketplace, to detect our consumer sentiment about those products and services, to acquire us as customers, to solidify our loyalty to their products, to predict our behaviors, and to amplify the effectiveness and ROI of their marketing investments.
Marketing: One lens through which we look at AI
Marketing has already been personalized to individual consumers for years, specifically through product recommendation engines. But these offerings are becoming much more data-informed than ever before. The volume of data, the depth of this hyper-personalization, and the breadth of market reach are not scalable with typical human-intensive techniques and tools. Marketing must rely on machine intelligence to carry most of that load, through data analytics, machine learning, and AI.
AI must not be considered as “artificial” intelligence, but as “augmented”, “assisted”, and “actionable” intelligence. That’s the real “AI” power. – Kirk Borne
In all of this, AI must not be considered as “artificial” intelligence, but as “augmented”, “assisted”, and “actionable” intelligence – that’s the real “AI” power. In those tough cases where the machine learning algorithms do not do well, AI will assist humans, and humans will assist the AI in delivering the right insight to the right person at the right time in the right context. We may even consider AI as amplified intelligence – that is true human-machine collaboration!
Clarity prevents misunderstandings
One of the roadblocks to implementing AI is that it has different meanings for different people, and consequently a lot of misunderstanding about what it is, how it is being used, and how it can be used. AI may bring to mind these meanings: chatbots, robots, natural language processing, sentiment analysis, predictive analytics, pattern (facial, voice) recognition, autonomous vehicles, robotic process automation, automatic product recommendations, supply chain optimization, smart cities, traffic routing, etc. Those who develop and deploy AI technologies must explain clearly to their stakeholders what they are doing, how, and why.
Marketers can use machine learning and AI to better understand their data: for example, to find informative and actionable correlations, trends, segments (clusters), anomalies (novelty, surprises), connections (links, associations), emerging patterns, and important features in their data. This includes static patterns in the data (representing persons, locations, and items of interest), but it also includes dynamic patterns (representing behaviors of interest, movements of interest, emergent phenomena, and trends of interest).
The [organization] that derives the most value from their data is the one that wins. – Kirk Borne
The organization that has the most data is not the one that wins. The one that derives the most value from their data is the one that wins. Value creation from data includes discovery of relevant insights and taking effective actions based on those insights. AI and machine learning enable that winning combination of relevance and effectiveness.
Will AI cause job loss?
AI and machine learning will enrich marketing, making it more personalized, productive, and powerful. That does not necessarily mean that marketing jobs will go away, but it does mean that the human work required for those jobs will change.
Tomorrow’s marketer’s work will be more machine-assisted, data-informed, and insights-driven. The marketer will still be needed to provide the personal touch, the subject matter expertise, the guardianship over proper algorithm behaviors, the stopgap against bias creeping into algorithms, and the historical perspective that is key to most successful marketing. Other industries are facing similar questions and challenges, and the same requirement for humans-in-the-loop will continue in those industries also.
The raison d’être of big data, machine learning, and AI is not to reduce job opportunities, but to change and enhance job opportunities in productive and fulfilling ways. We expect to see these new roles and the increasing role of AI in such fields as healthcare, manufacturing, customer service, financial services, retail, cybersecurity, and (of course) marketing.
Now, take the conversation to Twitter! Agree or disagree with this perspective on artificial intelligence? Want to ask Kirk a question? Tweet @KirkDBorne using the hashtag #datamakespossible right now!
Certain blog and other posts on this website may contain forward-looking statements, including statements relating to expectations in the market for our products and applications of our products. These forward-looking statements are subject to risks and uncertainties that could cause actual results to differ materially from those expressed in the forward-looking statements, including development challenges or delays, changes in markets, demand, global economic conditions and other risks and uncertainties listed in Western Digital Corporation’s most recent quarterly and annual reports filed with the Securities and Exchange Commission, to which your attention is directed. Readers are cautioned not to place undue reliance on these forward-looking statements and we undertake no obligation to update these forward-looking statements to reflect subsequent events or circumstances.