Arden University recently held a webinar with faculty member Dr. Iain Rice, discussing the extent to which Artificial Intelligence is affecting the modern workplace. Dr. Rice also explained how Arden’s online master’s programmes help you gain the knowledge you need to work in this exciting area of computing and IT. Read Dr. Rice’s interview below, and follow the link above to watch a recording of the full webinar.
What is Artificial Intelligence?
Artificial Intelligence (AI) is actually a bit of a misnomer – its meaning depends on who you are, which changes your idea of what it is, does, and means. To some, AI is a panacea for the future of the organisation – able to understand images better and faster than humans, able to drive cars in a complex world without causing accidents, or able to make that next investment decision in a fraction of the time a human could.
To mathematicians, however, AI is often nicknamed ‘Actual Idiocracy,’ not least due to the size of the field--in terms of research, development, and application. Mathematicians also question the wisdom of calling artefacts intelligent, when in fact they are merely effecting a set of simple mathematical operations with no evidence of sentience in sight. A case in point for this is one of Google’s famed image recognition systems, the building blocks of which utilise the ‘y=mx+c’ line equation, which many of us learned at the age of 12!
Ultimately, AI takes information in the form of data, and turns that data into a decision. It is the speed and accuracy of those decisions that is meant to improve our lives in one way or another.
What is the foreseeable impact of AI on the future of work?
If we parallel AI with other technological revolutions such as combustion-based engineering, the automated assembly line, computer-based documentation and communication and agile software development, we’ve seen that AI could be a disruptive force in the status quo of work.
In making quicker decisions with higher accuracy than current systems and humans, we could see development and competition improve rapidly within and between organisations. Of course, there will be a set of jobs currently undertaken by humans which could be ‘lost’ to AI, but AI is not the enemy here. Rather, it is a technological development requiring human initiation, monitoring and management which the workforce has to respond to.
People need to upskill--and fast—to change the way they work. So, for example, instead of carrying out the role of marketing analyst to extract patters from current trends, marketing professionals will need to present the outputs of an AI process which do this analysis. This requires knowledge of the limitations of current AI systems and knowledge of what is being inferred. This is why our analytics programmes at Arden are applied to key areas where people integrate with AI, such as operations management and digital marketing. AI, in its current form, can make work more efficient, but it will not remove the need for people in the workplace for a very long time.
What companies are pioneers in the AI field?
This is a really interesting question. You’d think that the pioneers would be the big tech giants – Google, Apple, Huawei, Facebook and the like – and to an extent you’d be right. However, what’s actually happening on the ground is that small companies starting out in a niche area using AI to solve a single, or small set of problems, are producing some of the greatest innovations, which large organisations can’t match.
A great example of this is Darktrace, one of the most innovative companies working in computer systems security. Darktrace started out as a small band of people who left their jobs at GCHQ, the British intelligence agency. Armed with more than a bit of knowledge about AI and cyber security, they are now a world leader in the field. DeepMind is another example of an organisation that started out with a small, niche aim, and jumped to the forefront when they were bought by Google, who assimilated the company’s knowledge and skills rather than trying to beat them at their own game.
How do organisations begin to incorporate AI systems into their operations?
Firstly, organisations need to identify what data they have. This is a requirement for AI; without data, AI in its standard format will not yield any results or insight. Once the data is there, the organisation needs to ask what it wants from AI – faster decisions, better results, or support for staff in decision-making, for instance. Organisations then need to bring in specialists, if they don’t already have them, to take the data and implement a form of AI to see how effective it is.
If the thresholds for performance are met, then the AI system can be implemented and maintained while performing the role. Staff training is an important aspect here; we naturally distrust computer developments which don’t seem to offer a clear benefit to daily life, as Alexa has, for example.
For systems managers, data experts, and programmers, what are the career paths in AI?
People think you need to be either a data analyst or a computer scientist to enter the world of AI, but in reality the career pathways are as broad as for any computerised systems.
Initially, an AI system needs to be designed to carry out a specific task, which requires an application expert with a computing background, and a data scientist to design the AI system to fulfil that job. A data analyst will need to test the effectiveness of that AI and work with both the application expert and data scientist to check the results meet benchmarks. From this, a programmer will need to embed the AI into the specific system performing the role. In most cases now, the system will have online access or usage, requiring a cloud computing expert. As soon as anything is online, or accessing data independently as AI does, an IT security officer will need to be involved to verify that security standards are met. This team will need to be managed by an IT professional with knowledge of the whole process chain for AI creation, implementation, and maintenance from a strategic point of view.
External to this is the business and operations side of things, which integrates with the AI aspects. If the AI is replicating a business role in an organisation, then staff will need training and managing through this. If the AI is part of an external offering, then it will need to be sold through marketing teams or implemented with partners though relationship managers and business development.
Everyone involved in these stages will have their careers changed and developed by AI, and in this example we’ve only assumed a small application requiring a single individual in each role, rather than the teams of ten or more that would typically be involved in a medium-sized project.
How do Arden University's online Computer and Data Analytics programmes reflect current practices?
Arden’s online MSc programmes touch key strands of the job roles I just mentioned. Our Data Analytics programmes teach learners how and where AI can be implemented, how it should be evaluated, and how results can be presented to business and marketing professionals. Furthermore, these MSc programmes are coupled with key areas such as enterprise architecture, finance, human resource management, information systems management, IT security management, marketing and project or operations management.
Therefore, our learners can appreciate the importance of where AI is being applied. Beyond these aspects, the surrounding, connected roles are covered by our IT master’s online programmes. Our courses in enterprise architecture management, IT security management, and strategic IT management are where learners will see how AI can be integrated, maintained and protected in a variety of organisational paradigms. These programmes are constantly updated to reflect current developments and challenges within AI.
Who are our programmes designed for?
Quite literally anyone wanting to get into AI and the wider IT field and who has the relevant undergraduate qualifications or work experience. In fact, our data analytics programmes assume no prior knowledge of data analysis. They just require that you are enthusiastic and willing to get stuck into the field, and engage with both the wider reading and applied exercises necessary to succeed in analytics. Our IT postgraduate programmes take a management perspective, so approximately two years of experience in IT is necessary. Having said that, our students often benefit more from their studies when they have more experience and are performing some form of management role in the IT sector.
What are the benefits of studying your masters online?
There are two significant benefits to studying online – flexibility, and peer learning. Our degree programmes are asynchronous, meaning they can be studied anytime, anywhere and at a speed to suit the learner. One of the great aspects of an Arden programme is that you can learn not only from the material and your tutor, but also from other learners. Through discussion and group activities you can see how individuals across the world have, or would, react in certain situations. You can get a new perspective of what you’re doing in your organisation and learn to challenge some of the fundamental principles which may be holding everyone back.
To find out more about Arden University’s range of online master’s programmes in computing and IT, take a look at our related programmes.
MSc Data Analytics and Information Systems Management
This master’s degree programme develops your ability to interpret, analyse and manage big data, giving you a skillset sought-after by businesses worldwide.
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