How Thinking Fast and Slow Delivers Smarter IoT Solutions
In his book Thinking, Fast and Slow, Daniel Kahneman, Nobel Memorial Prize in Economic Sciences laureate, describes two different ways our brains process thoughts:
- Thinking fast, where you need prompt decision-making and don’t have the luxury to do long-term strategic thinking. Examples: stopping at a yellow traffic light, shaking someone’s hand.
- Thinking slow, where the consequences of your decision may have long-term implications and you need to deliberately take the time to think. Examples: the car you’re going to buy, whether to change jobs.
Both of these types of thinking, fast and slow, are absolutely critical for our survival.
Data Is the New Gold, But…
What does this have to do with the Internet of Things (IoT)?
It’s surprising how much cognitive computing and IoT computing have in common. While we’ve all heard that data is the new gold, we also have to be aware that not all data is created equal. Even with the best of data, if we don’t know how to differentiate between data types, we’re not only going to drown in data but we’ll also make catastrophic decisions.
Thinking Fast in IoT
When evaluating IoT deployment options, it is critical to understand the difference between operational data analysis for immediate action and strategic data analysis for longer-term business decision-making. Consider the automatic emergency braking that prevents a vehicle-to-vehicle crash, or an implanted medical device (such as a pacemaker) that saves a patient’s life: These are examples of operational data analysis, or thinking fast in IoT. This type of data processing often occurs in a time-critical and harsh environment where Internet connectivity may be poor or unavailable.
In these examples, operational data analysis needs to happen within milliseconds, or else something fatal could potentially ensue. There’s no time to send the data to a cloud server because of latency issues, so the data must be analyzed at the edge, close to where it originates.
Thinking Slow in IoT
Thinking slow in IoT is pretty straightforward. It’s mostly about data analysis for important and strategic decisions that have broad, long-term impacts. Examples of thinking slow include a car rental company looking to optimize asset utilization, or a pharmaceutical company reducing the time to market for its new cancer drug through IoT-enabled clinical trials. Although the decisions are very important, there’s no urgency to obtain answers immediately because they do not stop the business. Since the amount of data needed for these strategic decisions is vast, it only makes sense that the data is transferred to the cloud for in-depth processing and analysis. When evaluating IoT use cases, think slowly about edge versus cloud computing needs.