Category Archives: Artificial Intelligence

The fourth industrial revolution and what this means for medicine

Individual technology advancements have been vast for the last 100 years, however, the convergence of these technologies we are seeing over the last few years, the speed, the velocity and disruption of change is something which has never been experienced before

To put in context, what is today the widely adopted telephone took around 70 years to really penetrate the majority of households. The personal computer was around for 20 years before it became widely popular. The iPhone took Apple just 6.5 years to reach the penetration of half a billion in a global audience. In more recent years the likes of Uber are now collecting data points of over 40 million monthly users as we go about our daily business. For Facebook in the 13 years, it has been around, has become now the 2nd biggest organisation (in terms number of members) on the blue planet, only a small margin behind to the entire combined Christian religious sects of the world! So it’s clear the speed and intensity that technology is swarming over us is only increasing.

The 4 waves

The 1st Industrial revolution in the 19th century broadly brought in the era of automated machines, mechanical innovations and large metal industrial machines which changed the landscape for factory workers and industry

The 2nd Industrial revolution brought around the ability to mass produce through assembly lines and electrification

The 3rd industrial revolution through the 1970s to the early noughties brought mainframe computing, personal computers and the internet

Today we stand on the doorstep of the 4th industrial revolution where radical system-wide innovation can happen in only a few years. The intersection of nanotechnology, artificial intelligence, 3D printing, IoT sensors and computing power will create realities which we have previously thought unthinkable. Access to technology will mean almost anyone will be in a position to create new products and services cheaply and with rapid pace – this will disrupt and change the business model of each and every industry.

As the technology moves so fast, and the wave of excitement (by some) gears up to the possibilities ahead of us, It is important to ensure that we take stock, and ask the ethical question to ensure that this is used ‘for the good’. The balance between what we stand to win and what we might lose as a society is for another debate, but one thing for sure is that we must ensure that this evolution happens with humans centred at the core of it and not the technology. Much of the bad press that some of these technologies (such as Alexa recording a private conversation or the driverless car causing injury or death) are obviously not to be ignored, so ensuring that regulations and a universal code of ethics are established along with the technology development is equally as important in my view.

‘The only constant is, change’

But what could this mean for the healthcare industry, a $7.5 trillion global annual spend industry? Few industries have the potential to be changed so profoundly by digital technology as healthcare, but the challenges facing innovators – from regulatory barriers to difficulties in digitizing patient data – should not be underestimated.

By almost any measure, global health has improved dramatically in recent decades. However, the current model for providing healthcare is being slowly torn apart by the opposing forces of an ageing population and greater restraints on government spending.

However, the revolution of technology which has built such momentum in the social conversation through the decades has provided an umbrella to another revolution which has unassumingly been happening – the genetics revolution!

Similar to technology, the human genome is an information processing device; just one produced by biology and evolution rather being programmed with a computer. The 4th industrial revolution will also power the automation of biology, and we stand on the cusp of an incredible take off of genomic technology.

Today, 4% of the world’s data collected is in health data, a relatively low percentage of the overall data collected. But this is changing…fast. By 2030 it is predicted that 41% of the world’s data collected will be related to health. With the application of various techniques from the Artificial Intelligence world to allow for large-scale biology automation, this is posing questions, both quantitatively and qualitatively, that have never been asked before. What is a disease for example, and how does this manifest itself against different genotypes? Rather than a blanket, one-size-fits-most approach, medical professionals will be able to personalize the treatment choices for patients based on a dataset consisting of information that is extracted from your genetic profile (which you have inherited from your family), your daily habits, where you live and other environmental factors. The cost of reaching these outcomes has dramatically decreased also. Decoding the first genome in 2004 costs hundreds of millions of dollars yet by today’s standards, machines can sequence 18,000 annually for around $1000. Companies or initiatives like 23andme have brought some aspect of DNA profiling to the consumer market while the ‘quiet’ revolution in the deep genetic profiling space by companies such as Foundation Medicine and Helix, is paving the way for a real revolution in healthcare and medicine as we know it.

Digital and healthcare are at the core of what we do at Nitro. We love to get into these aspects and how we can help realise, with our partners, the challenges intersecting digital and healthcare. These two frontiers will continue to collide, and ensuring that we do all we can to adhere to the basic principle of ensuring that we keep the human user at the heart of it all and, solve problems for the ultimate good.

Get in touch we’d love to chat more on this or tell us what you think?

 

The voices you can’t ignore

From the first WAP phones of the late nineties (Nokia 7110 anyone?), and the introduction of the game changing iPhone in 2007, the idea that users can have on-demand connectivity to the internet on a portable device has led a drive for better, faster devices. Before the iPhone, the trend was ‘the smaller, the better’, but with today’s feature rich devices, the image quality and resolution is important. Screens are getting bigger, but to what end?

While screens are getting bigger, using a keyboard on a phone is not getting any easier. We can’t wait for human evolution catch up, and our fingers become small enough to interact with these devices easily.

Luckily, we don’t have to wait that long, as voice services are here. For several years, the technology just hasn’t been there to allow a machine to understand what you say to it. However, that piece is generally agreed to have been cracked (with some notable exceptions), and with the release of services such as Amazon’s Transcribe to the developer community, it’s never been easier to convert speech to text, and to build these services into our apps and devices. Machine learning as a service allows the transcriptions to get better over time, as the systems learn and build contextual vocabularies to make these faster, more accurate, and with a far higher degree of confidence.

The Growth of Voice

This has been, and will continue to be, much more of a sea-change than the mobile ‘revolution’ has been. Considering how slowly the need for mobile-first, responsive websites was realised amongst brands and creative agencies, the rapid emergence of voice searches is something that can’t be shrugged off. At the very least, if you’re not optimising your web assets for voice, you will be left trailing in the wake of those brands that do. Consider the following statistics:

“50% of all searches will be voice searches by 2020”, according to comscore

“As of January 2018, there were an estimated one billion voice searches per month”, according to Alpine.AI.

“60% of people using voice search have started in the last year”, according to MindMeld

“We estimate that 325.8 million people used voice control in the past month”, according to Global Web Index

“47% expect their voice technology usage to increase”, according to ComScore

If you want this massive potential audience to discover your content and engage with your brand, you have to act now.

This doesn’t mean just making your web pages ‘readable’. Publishers already understand that content needs to be optimised for mobile, and the same is true when delivering your content in response to voice searches. A predominantly mobile audience does not want to be presented with a lot of hi-resolution video content, and audio users certainly don’t want to be presented with pages of turgid prose. Audio optimised pages need to be highly relevant, concise and punchy in tone, not delivered like a lecture.

Every piece of content you publish must have not just a omni-channel audience in mind, and publishers need to be aware of the need to engage with their audience in different ways at different times. This presents a challenge to publishers, but it is one that is easily met. There are many Content Management Systems that can publish ‘versions’ of a page, but these are mostly oriented at a visual audience – delivering different content depending on device type and/or screen size.

Where to start?

The open-source content management framework Drupal, in its latest release, has opted to largely separate the Content aspect from the delivery piece. This means Drupal is more than just a tool for building websites (indeed, if that’s all you want to do, Drupal is probably not the solution you are looking for). Drupal is built with integrations in mind, and supports a large number of APIs straight out of the box. This API-first approach means you can have a central application, publishing content to all of your channels; traditional web, social media, mobile apps and voice searches. You can build your applications in any technology you want – and your users will never have to interact with Drupal at all. This separation of the content from the presentation is known as headless, or de-coupled architecture, and is the way forward.

Drupal is an ideal tool for the job. You can construct content that have ‘flavours’ optimised for any audience, whoever and wherever they are. A properly architected system allows you to track any individual’s interaction with all of your content, on all devices.This helps you build a very detailed profile of all of your viewers. This insight allows you to further personalise the experience, delivering the content your audience wants. Utilising machine learning algorithms, you can constantly improve this experience over time.

We’re technology agnostic but solution focused

Nitro Digital have been working with Drupal for over 6 years. We have a number of highly skilled, Acquia certified developers, site Builders and Solution Architects with a combined experience of nearly 60 years. We can help you achieve the outcomes you want, and look forward to understanding your problem in more detail.

Please call us on +44 (0) 207 148 6821, or contact us here to talk to an expert.

Why Pharma marketers need to know about AI….and how to get started

The writing is on the wall.

Marketers at all levels, in any discipline and industry, need to understand AI. Artificial intelligence is about to transform and disrupt marketing as we know it.

Why?

Because your upcoming strategic initiatives will increasingly involve AI and related technologies. In fact, they might already.

That’s a bold prediction I know and an easy one to make but I’m confident of this for several reasons.

1. AI investment is exploding.

The AI space is flush with money. There has been a 4.6X rise in deals to AI startups since 2012, reports CB Insights. In that time, equity funding of almost $15 billion has flowed into AI companies. In Q1 2017, 48% of deals were seed or angel deals, which indicates large numbers of new firms entering AI.

CMO’s around the globe are widely trying to figure out how it fits into their 2018 strategies. And they don’t want to get left behind by competitors who grasp AI faster.

Alphabet (Google’s parent), Amazon, Apple, Facebook, IBM and Microsoft are investing huge sums to develop their AI capabilities, as are their counterparts in China which is an indicator and driver of this trend as powerful as these technology galacticos are.

AI’s moment and its general public consciousness is here and unfolding before our eyes. And marketing is one of the top areas where it will make waves in 2018.

2. AI-enabled marketing companies are here.

Marketing is waking up to AI. More than 3,500 marketing leaders say AI is where they see the most growth potential in the next two years, says Salesforce.  We’re seeing more companies launch marketing AI tools or expand the use of AI in current offerings.

This reflects what happened when AI disrupted finance in the 1980s, as detailed in Scott Patterson’s book The Quants. It started when quants used algorithms to automate trading. The machines did a better job than the humans and the people who built the machines profited. Today, the majority of trades on Wall Street happen thanks to AI.

Healthcare is experiencing a similar moment now, though in a different fashion. X-ray and medical data analysis are being performed by AI systems now.

The jobs of doctors and specialists are being augmented and enhanced by AI. Spectrum is actually assessing use cases here and keeping an eye and a score to which therapy areas and specialities are being challenged by AI and who is winning.

Veeva being the CRM software platform of choice for many pharma companies could be a great long-term artificial intelligence (AI) hedge. Granted, the company isn’t doing a tremendous amount in AI right now. However, the key to AI is data – and with its growing number of applications and customers, Veeva has more data in its niche market than anyone else. One analyst asked Peter Gassner (Veeva CEO) on the last earnings conference call about the potential for the company to widen its moat over the next three to five years by applying AI to its data. Gassner said the company had plans to do just that.

As Christopher Steiner wrote in Automate This, “Determining the next field to be invaded by bots is the sum of two simple functions: the potential to disrupt plus the reward for disruption.” And the health space has all that!

It’s marketing’s turn. There exists a double incentive for AI companies to disrupt marketing. Marketing can be expensive. Cost-savings without sacrificing performance reflect well on executives. Second is that marketing activities directly impact the bottom line. For many other activities, this isn’t necessarily so pressing, for example, it doesn’t matter whether a human or AI lawyer assesses a contract, as long as it’s accurate. The cost is what matters here. But in marketing, AI has the potential to both reduce cost and improve ROI.

This makes marketing especially attractive for AI disruption. AI improves standard productivity. But it might also be able to do a better job than some human marketers at producing profit-driving results.

3. Big players in pharma marketing and sales category are becoming AI-first companies.

Pharma is already turning to AI to help revolutionise their R&D process and it won’t be long before the use of AI in how they market these developed molecules plays a part all the way through the marketing franchise.

Major marketing and sales companies are exhibiting this shift. Adobe Marketing Cloud introduction of Adobe Sensei has positioned itself as an AI player. Focusing on using AI to drive personalisation of content, this technology will begin to absorb itself into some of the uses of Adobe Campaign, Adobe Target and other in the pharma adopted marketing suite.

Salesforce is another major AI player. The company is baking its Einstein AI into every part of its existing product, and considering that Veeva is built on a Salesforce platform there’s a good chance that your marketing automation or CRM platform has AI or plans for AI in 2018 as alluded to by Veeva CEO

So, this begs the question:

Why should marketers care? AI will become widely available in existing platforms and new, accessible tools. Isn’t that enough? Why do marketers need to spend time and energy really understanding AI? Won’t the machines just help us do our jobs better?

Yes, they will. To start. But marketers need to understand AI because, if they don’t, AI could start doing their jobs next.

Why Marketers Need to Learn AI Now

AI capabilities improve year after year. Today’s marketing AI may simply augment your job, freeing you up to do the tasks only humans can do. That’s great. But next year, AI might be able to do more tasks that only humans can do. The year after, it might be able to do most of what you do today.

How do you create value in the marketing world a few years from now? Chances are, you don’t just do one thing in your organization. You might define strategies, create and promote content, schedule social promotion, and measure performance. You might also run paid and email campaigns, score prospects or drive marketing optimisation.

Now, what if AI can do all that? Where does that leave you?

It’s the future we’re approaching at a headlong pace. And it’s possible, actually, highly probably, future AI-empowered marketing teams can do more with fewer people.

Marketers must evolve to meet the approaching age of AI. They must learn to master the machines, rather than the other way around. And they must use AI to drive performance, rather than sit on the sidelines.

AI champions within organizations will become indispensable. They will guide executives on how to harness this technology for massive gains.

Change is happening fast. But there’s good news.

You don’t need to learn how to program or build AI systems to become knowledgeable. You can start becoming a recognized AI authority in your company by taking these steps:

1. Demystify the bulls**t

Like many of the buzzwords that surround our industry, AI is an easy one to latch onto and band around without a great deal of understanding to what it actually is. Artificial intelligence (AI) is a broad term that refers to the process and result of teaching machines to perform intelligent tasks. “Artificial intelligence,” far from being just a branch of computer science, is an umbrella that covers many different fields and technologies, including machine learning, deep learning and the programming of neural networks. Yes, the topic can be complicated but seek out help to get down to the basics and principles that will help with the knowledge adoption of this for you and your peers. We have run some really useful and simple ‘AI Introduction workshops’ with clients that are wanting help to understand the foundations and a starting point of this a bit more.

2. Start with use cases.

Too many people start out with AI by trying to fit a round peg in a square hole. AI isn’t the right fit for every marketing use case, so don’t try to use tools only because they’re AI. Instead, identify the marketing problems you’re trying to solve in your organization.

What do you struggle with daily? What strategic priorities are important for the next couple quarters? What are your performance goals (New leads? Visits? Higher sales?). What activities take you away from the work you should be doing? Make a list of these. Then begin your research by searching for these terms or problems and including the term “AI.”

3. Begin experimenting.

There are dozens of AI marketing tools you can start testing for free. Start by signing up for trials and demos. There are a lot of hyperbolic claims out there about what AI tools can and can’t do. And they’re not always accurate. You’ll need to do your homework and see for yourself what a company offers and how it can help you achieve those goals. Run a small pilot to prove a hypothesis. This is a great way to test and learn before you commit resource to accelerate here.

4. Talk with people who understand what they’re talking about.

Don’t be afraid to ask questions of solutions providers or your digital agency partners. The marketing AI community is full of people who are passionate about AI’s potential. Most are happy to talk through your questions and use cases, even if you’re not ready to buy anything.

Also, don’t hesitate to contact us here at Nitro DIgital for any of these needs either.

5. See what your current tools have to offer.

There’s a good chance your marketing automation or CRM system incorporates AI in some way or will be soon. Search online for ways your software uses AI. You might also ask your account rep how each tool uses AI or what the company’s AI roadmap looks like.

6. Play around with the AI in your personal life and understand better how it works.

You’re almost certainly already using or benefitting from AI in your personal life. Netflix recommendations use AI and machine learning. So do Amazon product recommendations. Siri or Alexa voice assistants use AI technologies to field and respond to your queries. Google search relies heavily on AI to suggest the best results.

Start researching how these everyday tools do what they do. There are tons of resources out there on popular tech tools and how they use AI. Everyday AI tools give you an accessible way to start understanding the technology.

7. Rely on the right resources.

Like I’ve mentioned, there’s a ton of AI hype out there. Like any popular subject, sensational headlines abound. On any given day, there might be hysteria that AI will turn into killer robots. Or that it will make everyone jobless starting tomorrow.

AI is powerful and transformative. But most headlines and stories on it want you to click, not think.

That doesn’t mean there’s not a lot of quality information available. Sometimes, you just have to dig for it. But find the right information, and you’ll save a ton of time. You’ll also gain a solid grasp of what AI actually can and can’t do. This will help you connect the dots of what’s possible in your own business.

Lastly the phrase ‘Leaders are readers’ is ever so true. There are some great books available on the general AI topic if you want to throw yourself in and get ahead. Here’s a short list of some of our teams recommended favourites;

The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World by Domingos, Pedro (September 1, 2015)

Automate This: How Algorithms Took Over Our Markets, Our Jobs, and the World

Surviving AI: The promise and peril of artificial intelligence