Strategy & Planning - Course

Big Data and Analytics

Free Lesson
Global Authority

The Global Authority

12 years delivering excellence

Members

75,000 + Members

Join a global community

Certification

Associate Certification

Globally recognised

Membership

Membership Included

Toolkits, content & more

Digital Marketing - Study Notes:

What is artificial intelligence?

Artificial intelligence (AI) is the theory and development of computer systems able to perform tasks normally requiring human intelligence such as individual perception, speech recognition, decision-making, translation between languages. It’s the cognitive processes that machines can use as a way to make key decisions based on key real-time inputs that are being had.

A very simple basic example is that of HSBC implementing voice and speech recognition into the internet telephone banking core services. It enables people to actually just have a voice recognition to be able to access their balances. This is a great, interesting way of using artificial intelligence. However, artificial intelligence can be used across a multitude of different facets, from core everyday things like telephone banking all the way through to putting robots on Mars.

Catalysts for progress

What are some of the catalysts for growth when thinking about artificial intelligence?

  • Moore’s Law: Moore’s Law is the idea that people have an 80/20 rule. The relentless increase in computing power available at a given price and size, sometimes known as Moore’s Law (after Intel cofounder Gordon Moore). This has benefited all forms of computing, including the types AI researchers use. A pertinent illustration of this is that the current generation of microprocessors deliver four million times the performance of the first single-chip microprocessor introduced in 1971.
  • Big data: There is a lot of data out there now, including big data. You can make key decisions based on this. And that’s driving intelligence through the system because of the ability to kind of put data sets together to create what we think is going to be predictive.
  • Internet and the cloud: That gives you the tools and the know-how to create networks of connectivity. We talked about the Internet of Things and that’s starting to play at the forefront of artificial intelligence in this way.
  • New algorithms: New ways of thinking about things enables you to create better decision-making processes within the operations that you have. So in the likes of advanced robotics for example, ultimately it’s the algorithms which then start to help to determine what the next best action is. Now what is changing is the dynamic nature of those algorithms, because clearly once one is done machine learning enables the art of being able to then process it, and create new dynamic algorithms for the next experience. So not only is it static and it’s only based on the inputs at one point in time, it’s starting to become way more dynamic. And this is changing and it’s becoming much more robust down the line basically, as well.

Common applications

Common applications include finance, hospitals and medicine, customer services, transport, and telecommunications. Associated technologies include computer vision, machine learning, natural language processing, robotics, and speech recognition. Reflect on this and do a little bit more research about how AI can actually influence your world and what basically it’s doing. You can reflect on how AI is kind of coming into your work, basically.

Social considerations

But with AI you just start to kind of have these reflections of The Terminator, and Arnold Schwarzenegger and I, Robot, the Will Smith movie, and so on. So there are some real social concerns that you have to think about with the implementation of AI and how it then starts to get implemented into everyday life here.

Certainly, these are some things that are top of people’s minds, especially when you start to marry up things like privacy data and when machine learning starts to take over and make cognitive decisions on its own back. We need to be kind of conscious about some of the implications of that.

  • Employability issues: One of the key things that even in this current regime people are not sort of worried too much more about globalization, about causing employability issues, but when machines start to take over the jobs that are in the environment. So how do we then transfer going to the next revolution on from what we’re in today, to make sure that people have sufficient jobs? And automation doesn’t basically render us all unemployed.
  • Inequality: Clearly there’s some winners and losers within this game. We need to think about how sort of high-intensity capital versus lower-intensity capital kind of placed together in terms and measures together to reduce the inequalities.
  • Humanity: Consider the humanitarian aspects of things. Clearly one of the major applications of advanced AI is that in surveillance and even things like in terror zones or war zones, for example. Humanitarian aspects of things include whether it’s right for these things to be used in those vulnerable environments.
  • Robotic errors: You’ve had some interesting examples, where even the most robust technologies around, say, Tesla cars, have had fundamental errors and have caused significant damage. So thinking about the robotic errors that can occur, and basically solving for them.
  • Software security: We need to make sure that we recognize the aspects around security and then solving for those problems.

Economic considerations

What does AI allow us to do? And what are the implications?

  • Faster decisions: AI enables faster decision making. You can make faster decisions at speed and respond to that in a quicker way.
  • Lower costs: It also enables lower costs because clearly less decision inputs, manual sort of inputs in there.
  • Better job allocation: You can focus the people on less manual tasks and get machines to do all the rest.
  • Greater scale: You can basically upscale your operation in a much more robust way, and with a lot less variability. Which you do have when you’re thinking about manual intensive type of approaches.

Technological singularity

This is the hypothesis that the invention of artificial superintelligence will abruptly trigger a runaway technology growth, which will result in unfathomable changes to human civilization.

This goes back to the Big Brother approach, The Terminator approach, the I, Robot approach. This fundamentally shifts the way that humans operate and live. The way that the economic model works, the way that we have employability, humanity, jobs, all of those kinds of key things will fundamentally change.

And this is a little bit of a trigger point in our time, to think about not only the advantages but how we overcome some of the significant disadvantages to the way these technologies will shift the way that we operate. And more so, that we don’t leave people behind, this inequality factor is going to become very important for the future. So being cognizant about that and thinking about that is going to be really important.

Back to Top
Richie Mehta

Ritchie Mehta has had an eight-year corporate career with a number of leading organizations such as HSBC, RBS, and Direct Line Group. He then went on setting up a number of businesses.

Richie Mehta

Data protection regulations affect almost all aspects of digital marketing. Therefore, DMI has produced a short course on GDPR for all of our students. If you wish to learn more about GDPR, you can do so here:

DMI Short Course: GDPR

If you are interested in learning more about Big Data and Analytics, the DMI has produced a short course on the subject for all of our students. You can access this content here:

DMI Short Course: Analytics

The following pieces of content from the Digital Marketing Institute's Membership Library have been chosen to offer additional material that you might find interesting or insightful.

You can find more information and content like this on the Digital Marketing Institute's Membership Library

You will not be assessed on the content in these short courses in your final exam.

ABOUT THIS DIGITAL MARKETING MODULE

Big Data and Analytics
Richie Mehta Richie Mehta
Skills Expert

This module dives deep into data and analytics – two critical facets of digital marketing and digital strategy. It begins with topics on data cleansing and preparation, the different types of data, the differences between data, information, and knowledge, and data management systems. It covers best practices on collecting and processing data, big data, machine learning, open and private data, data uploads, and data storage. The module concludes with topics on data-driven decision making, artificial intelligence, data visualization and reporting, and the key topic of data protection.

Content Locked

Want to know more about this course?
Check out the full course details or sign up for a FREE course trial, and get access to more great content to help you level up your digital marketing career.

View Course Start a Free Trial