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Why Big Business Should Proactively Build for Privacy

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This article explores the rise of Privacy by Design (PbD) from the basic framework, to its inclusion in the GDPR, to its application in business practices and infrastructure especially in the wake of Artificial Intelligence.

We had the pleasure of sitting down with Dr. Ann Cavoukian, former 3-Term Privacy Commissioner of Ontario, and currently Distinguished Expert-in-Residence, leading the Privacy by Design Centre of Excellence at Ryerson University in Toronto, Canada to discuss this massive shift that will upend current business practices. We’ve also sought responses from top execs from AI start-ups, and enterprise to address the current hurdles and future business implications of Privacy by Design. This article includes contributions from Scott Bennet, a colleague researching privacy and GDPR implications on emerging technology and current business practices.

I call myself an anti-marketer, especially these days. My background has predominantly come from database marketing and the contextualization of data to make more informed decisions to effectively sell people more stuff. The data that I saw, whether it be in banking, loyalty programs, advertising and social platforms — user transactions, digital behaviour, interactions, conversations, profiles — were sewn together to create narratives about individuals and groups, their propensities, their intents and their potential risk to the business.

While it was an established practice to analyze this information in the way that we did, the benefit was largely to businesses and to the detriment of our customers. How we depicted people was based on the data they created, based on our own assumptions that, in turn, informed the analysis and ultimately, created the rules which governed the data and the decisions. Some of these rules unknowingly were baked in unintended bias from experience and factors that perpetuated claims of a specific cluster or population.

While for many years I did not question the methods we used to understand and define audiences, it’s clear that business remained largely unchecked, having used this information freely with little accountability and legal consequence.

As data becomes more paramount and as AI analyzes and surfaces meaning at greater speeds, the danger of perpetuating these biases becomes even more serious and will inflict greater societal divisions if measures are not put in place and relentlessly enforced.

Recently, I met my maker. Call it atonement for the many years I manipulated data as a marketer. We had the honour of talking Privacy with an individual I had admired for years. Dr. Ann Cavoukian, in my view, will drive a discussion across industry that will make business stand up and listen.

Remember when Canada’s Privacy Commissioner took on Facebook?

Ann Cavoukian has been an instrumental force in spreading awareness of Privacy, which brought her front in centre on the world stage, pitted directly against Facebook in 2008. Back then the federal Privacy Commissioner alleged that 22 practices violated the Canadian Personal Information Protection and Electronic Documents Act (PIPEDA). This eventually led to an FTC settlement with Facebook that mandated an increased transparency with its users, requiring their explicit consent before “enacting changes that override their privacy settings.”

Ann Cavoukian is a household name in technology and business. As a three-term Privacy Commissioner of Ontario, Canada, she has jettisoned the privacy discussion for a few decades. Today that discussion has reached a fever pitch as the EU General Data Protection and Regulation (GDPR), which came into effect May 25, 2018, includes Cavoukian’s long-advocated creation, Privacy by Design (PbD). This will raise the bar dramatically and any company or platform who does business with the EU, will need to comply with these standards. At the heart of GDPR are these guiding principles when collecting, storing and processing personal consumer information:

  • Lawfulness, fairness and transparency
  • Purpose limitation
  • Data minimization
  • Accuracy
  • Storage limitation
  • Integrity and confidentiality (security)
  • Accountability

Privacy by Design’s premise is to proactively embed privacy at every stage in the creation of new products or services in a way that’s fair and ethical. Cavoukian argues that by implementing PbD, companies would, in effect, be well on their way to complying with the GDPR.

What Makes this Moment Ripe for Privacy by Design?

In the 90’s the web was growing exponentially. Commerce, online applications, and platforms were introducing a new era that would dramatically change business and society. Ann Cavoukian, at this time, was in her first term as Privacy Commissioner of Ontario. She witnessed this phenomenon and was concerned it was going to grow dramatically, and in an era of ubiquitous computing, increasing online connectivity and massive social media, she surmised that privacy needed to be developed as a model of prevention, not one which simply “asked for forgiveness later.”

Imagine going to your doctor, and he tells you that you have some signs of cancer developing and says, “We’ll see if it gets worse and if it does, we’ll send you for some chemo”. What an unthinkable proposition! I want it to be equally unthinkable that you would let privacy harms develop and just wait for the breach, as opposed to preventing them from occurring. That’s what started PbD.

In 2010, at the International Conference of Data Protection Authorities and Privacy Commissioners in Europe, Cavoukian advanced the resolution that PbD should complement regulatory compliance, to mitigate the potential harms. It was unanimously passed. The reason?

Everyone saw this was just the tip of the iceberg in identifying the privacy harms, and we were unable to address all the data breaches and privacy harms that were evading our detection because the sophistication of perpetrators meant that the majority of breaches were remaining largely unknown, unchallenged and unregulated. As a result, PbD became a complement to the current privacy regulation, which was no longer sustainable as the sole method of ensuring future privacy.

These days the issue of data security has gotten equal, if not more, airplay. Cavoukian argues:

When you have an increase in terrorist incidents like San BernadinoCharlie Hebdo attacks in Paris, and in Manchester, the pendulum spins right back to: Forget about privacy — we need security. Of course we need security — but not to the exclusion of privacy!

I always say that Privacy is all about control — personal control relating to the uses of your own data. It’s not about secrecy. It drives me crazy when people say ‘Well, if you have nothing to hide, what’s the problem?’ The problem is that’s NOT what freedom is about. Freedom means YOU get to decide, as a law-abiding citizen, what data you want to disclose and to whom — to the government, to companies, to your employer.

Pew Research conducted an Internet Study post-Snowden to get a consumer pulse on individual privacy. Key findings cited:

There is widespread concern about surveillance by both government and business:
• 91% of adults agreed that consumers had lost control over their personal information;
• 80% of social network users are concerned about third parties accessing their data;
• 80% of adults agreed that Americans should be concerned about government surveillance.

Context is Key:

And while there are those who understand they are trading their information for an expectation of value, they should be fully informed of how that value is extracted from their data. Cavoukian cautions:

Privacy is not a religion. If you want to give away your information, be my guest, as long as YOU make the decision to do that. Context is key. What’s sensitive to me may be meaningless to you and vice versa… At social gatherings, even my doctors won’t admit they’re my doctors! That’s how much they protect my privacy. That is truly wonderful! They go to great lengths to protect your personal health information.

The importance of selling the need for privacy includes persistent education. Unless people have been personally affected, many don’t make the connection. Does the average person know the implications of IoT devices picking up the “sweet nothings” they’re saying to their spouse or their children? When they realize it, they usually vehemently object.

Context surfaces the importance of choice. It is no longer an all-or-nothing game subsumed under a company’s terms and conditions where one click, “Accept” automatically gives full permission. Those days are over.

And while some can object to analyzing and contextualization for insurance purposes, they may allow their personal health history to be included in an anonymized manner for research to understand cancers endemic to their particular region.

Context is a matter of choice; freedom of choice is essential to preserving our freedom.

Privacy Does Not Equal Secrecy

Cavoukian emphasizes that privacy is not about having something to hide. Everyone has spheres of personal information that are very sensitive to them, which they may or may not wish to disclose them.

You must have the choice. You have to be the one to make the decision. That’s why the issue of personal control is so important.

I extracted this slide from Ann Cavoukian’s recent presentation:

The <ahref=”https://www.wired.co.uk/article/china-social-credit” target=”_blank” rel=”nofollow noopener noreferrer noopener”>Chinese Social Credit System was created to develop more transparency and improve trustworthiness among its citizens. It’s a dystopia we do not want. China is a clear surveillance society that contradicts free society’s values. Cavoukian crystalizes the notion that privacy forms the foundation of our freedom. If you value freedom, you value privacy.

Look at Germany. It’s no accident that Germany is the leading privacy and data protection country in the world. It’s no accident they had to endure the abuses of the Third Reich and the complete cessation of their privacy and their freedom. And when that ended, they said, ‘Never again will we allow the state to strip us of our privacy — of our freedom!’ And they have literally stood by that.

Post-Snowden, I wrote this: The NSA, Privacy and the Blatant Realization: Nothing You Do Online is Private and referenced a paragraph written by Writynga in his response to Zuckerberg’s view at the time 2012 that privacy was no longer a social norm:

We like to say that we grew up with the Internet, thus we think that the Internet is all grown up. But it’s not. What is intimacy without privacy? What is a democracy without privacy?…Technology makes people stupid. It can blind you to what your underlying values are and need to be. Are we really willing to give away our constitutional and civil liberties that we fought so hard for? People shed blood for this, to not live in a surveillance society. We looked at the Stasi and said, ‘That’s not us.

The will of the people has demanded more transparency.

But we don’t want a state of surveillance that eerily feels like we’re living in a police state. There has to be a balance between ensuring the security of the nation and the containment of our civil liberties.

People will have Full Transparency… Full Control… Anytime

Since the passing of Privacy by Design (PbD) as an international standard in 2010 to complement privacy regulation, PbD has been translated into 40 languages. The approach has been modified to include the premise that efforts to ensure individual privacy can be achieved while developing consumer trust and improved revenue opportunities for business within a Positive Sum paradigm. Cavoukian is convinced this is the practical way forward for business:

We can have privacy and meet business interests, security and public safety … it can’t be an either/or proposition. I think it’s the best way to proceed, in a positive-sum, win/win manner, thereby enabling all parties to gain.

Privacy by Design’s Foundational Principles include:

  1. Proactive not Reactive: preventive not remedial
  2. Privacy as the default setting
  3. Privacy embedded into design
  4. Full functionality: positive sum, not zero-sum
  5. End-to-end security: full lifecycle protection
  6. Visibility and transparency: keep it open
  7. Respect for user privacy: keep it user-centric

Cavoukian contends that Principle #2, Privacy by Default is critical and, of all the foundational principles, is the hardest one since it demands the most investment and effort: with explicit requirements that change how the data is collected, used and disclosed, and will result in data policy and process alterations including new user-centric privacy controls.

Article 21 also states individuals have the “right to object” to the processing of their personal information at any time. This includes for use in direct marketing and profiling:

“The controller shall no longer process the personal data unless the controller demonstrates compelling legitimate grounds for the processing which override the interests, rights, and freedoms of the data subject.”

The business must be more explicit and go much further, beyond the traditional disclosure and terms of service. Purpose specification and use limitation require organizations to be explicit about the information it requires, for what purpose, and must elicit consent specifically for that purpose and that purpose alone. Later on, if a secondary use transpires, the organization will require the user consent once again. If disclosure is key to transparency, businesses will need to find a way to do this while mitigating consent fatigue.

Article 17 suggests a much stronger user right that belies current business practices: The Right to Erasure (“the right to be forgotten”)

The data subject shall have the right to obtain from the controller the erasure of personal data concerning him or her without undue delay and the controller shall have the obligation to erase personal data without undue delay.

While this statute will have exceptions like data that establishes the data subject as an entity: through health records and banking information, behaviour, transactions, future analysis in profiling, and contextual models are fair game for “the right to be forgotten.” The advent of the GDPR has provided business a glimpse of the potential impacts where companies experienced customer record volumes drop an average of 20% for customers who did not explicitly opt-in.

This is a truly user-centric system. Make no mistake, Privacy by Design will challenge current practices and upend current infrastructures.

This privacy UI simulation (IBM: Journey to Compliance) displays how potential user controls will work in real time and the extent to which the user can grant consent based on different contexts. This level of user access will require a data repository to purge user information, but must be configured with the flexibility to redeploy the data into systems down the road, should the user decide to revert.

 

Can Privacy by Design Create a Positive-Sum Existence for Business?
If you had asked me a year ago, I would have argued that Privacy by Design

is not realistic for business adoption, let alone, acceptance. It will will upend process, structure and policy. However, within the mandate of GDPR this is an inevitability.

We asked Ann Cavoukian to consider business practices today. Both Google and Facebook have received enormous fines in wake of the GDPR to the tune of $9.3 billion. Because of the recent Cambridge Analytica data breach, Facebook is investing millions in tools and resources to minimize future occurrences. It’s recent Q2 stock plummet took the market by surprise but for Zuckerberg, he made it clear they would be taking a performance hit for a few quarters in order to improve the platform for its users… not for its shareholders. While they are a beacon of how companies should behave, this clear “ask forgiveness later” model negated any appearance that this strategy was nothing less than altruistic.

Emily Sharpe, Privacy Policy Manager at Facebook contends that in preparation for the GDPR, they paid particular attention to the Article 29 Working Party’s Transparency Guidance:

We have prepared for the past 18 months to ensure we meet the requirements of the GDPR. We have made our policies clearer, our privacy settings easier to find and introduced better tools for people to access, download, and delete their information. In the run up to GDPR we asked people to review key privacy information which was written in plain language, as well as make choices on three important topics. Our approach complies with the law, follows recommendations from privacy and design experts, and is designed to help people understand how the technology works and their choices.

Cavoukian pointed to a study by IBM with the Ponemon Institutethat brought awareness to the cost of data breaches: It reports that the global average cost of a data breach is up 6.4 percent over the previous year to $3.86 million per incident. On a per record basis, the average cost for each record lost rose by 4.8% to $148. As Cavoukian points out, these costs will continue to rise if you maintain Personally Identifiable Information (PII) at rest.

The PbD solution requires a full end-to-end solution which includes both privacy and security:

  1. IT systems;
  2. accountable business practices; and
  3. networked infrastructure.

How Do You Address the Advertisers Who Successfully Monetize Data Today?

What do you say to advertisers and publishing platforms who play in this $560-billion industry? We can’t stop progress. The more data out there, the more demand from willing buyers to extract meaning from it. On the other hand, given the fallout from Facebook, some advertisers have been grey or black listed from advertising on the platform because of questionable practices or content. The platform changes have also significantly curbed ad reach opportunities for current advertisers. This domino effect is now compounded with mandates from GDPR to garner explicit consent and create greater transparency of data use. Ann Cavoukian said this:

The value of data is enormous. I’m sorry but advertising companies can’t assume they can do anything they want with people’s data anymore. I sympathize with them. I really do; their business model will change dramatically. And that is hard to take so I genuinely feel bad for them. But my advice is: that business model is dying so you have to find a way to transform this so you involve your customers, engage them in a consensual model where benefits will accrue to customers as well. Context is key. Give individuals the choice to control their information and gain their consent to exchange it for something they value from you.

Mary Meeker’s “Paradox of Privacy” points to the consumer’s increasing demand for products and services that are faster, easy, convenient and affordable. This requires systems that can leverage personal information to make this a reality for the consumer. Increased customization is the expectation but brings with it increased business risk. As long as current business practices persist, according to Cavoukian, it leaves their business vulnerable to, as we’ve witnessed, incessant data breaches and cyber attacks. Equifax and Target are two cases in point.

Communication with the data subject needs to be a win/win (positive sum). Can the business provide the necessary value, while respecting the choices dictated by the individual? When AI becomes more pervasive this will become even more challenging as streaming data will require more real-time interfaces and applications that allow access and individual configuration of data types across various contexts and vertical uses.

I asked a few executives from various data start-ups and from established enterprise businesses, who have had considerable business to consumer experience from advertising to social technology to network platforms, to weigh in on the privacy debate:

Josh Sutton, CEO of Agorai, was also former Global Head for Data and AI at Publicis.Sapient. In an advertising industry which drives hundreds of millions in revenue, the quest to build consumer relevance comes at a cost. This proliferates as more companies look to artificial intelligence to drive precision:

Data is clearly one of the most valuable assets in the world today — especially with the growing importance of artificial intelligence (AI) which relies on massive amounts of data. Data privacy needs to be incorporated into the fabric of how these technologies work in order for society to get the most benefit from AI. To me, data privacy means having the ability to control when and why data that you own is used — not the ability to keep it secret which is a far easier task. For that to happen, there needs to be open and transparent marketplaces where people and companies can sell data that they create, as well as a consistent set of regulations for how companies can use data.

Dr. Nitin Mayande, PhD, Chief Scientist of Tellagence, and former Data Scientist at Nike concurs with Josh Sutton. Nitin had been studying social network behavior for years and understands the need to transform current approaches:

Sooner or later I envision a data marketplace — a supply side and a demand side. Today, companies leverage data at the user’s expense and monetize it. The end user does not experience any real economic benefit. Imagine a time when data becomes so valuable the individual can have full control and become the purveyor of his/her own information.

For Dana Toering, Chief Revenue Officer at Yroo and former Managing Director at Adobe Advertising Cloud, his career saw the emergence of ad platforms, which heavily relied on treasure troves of data to gain increasing granularity for ad targeting:

As an entire ecosystem I feel we are just now coming to terms with the evolution of value exchange that was established between end users and digital publishers and software developers starting in October 1994 when Hotwired.com ran the internet’s first banner ad. The monetization of audiences through advertising and wide-spread data harvesting of the same audiences in exchange for ‘free’ content or software has enabled the meteoric growth of the internet and the businesses that are built around it but has also enabled massive amounts of fraud and nefarious activity. Thankfully we are at a tipping point where corporations/brands and users alike are taking back data ownership and demanding transparency, as well as consent and accountability. Defining and managing the core tenets of this value exchange will become even more important (and complex) in the future with the rise of new technologies and associated tools. So the time is now to get it right so both businesses and users can benefit long term.

I have had curious discussions with Dr. Sukant Khurana, Scientist heading the Artificial Intelligence, Data Science, and Neurophysiology laboratory at CSIR-CDRI, India. As an entrepreneur also working on various disruptive projects, he had this to say, echoing the above sentiments:

The debate between privacy and security is a misleading one, as the kind and amount of data shared with private companies and the government need not and should not be the same. AI has been vilified in data privacy issues but the same technology (especially the upcoming metalearning approaches) can be used to ensure safety while preventing unwanted marketing and surveillance. If the monitoring tools (by design) were made incapable of reporting the data to authorities, unless there was a clear security threat, such situation would be like having nearly perfect privacy. It is technologically possible. Also, we need to merge privacy with profits, such that by and large, companies are not at odds with the regulatory authorities. This means there needs to be smarter media and social platforms, which present more choices for data sharing, choices that are acceptable between the end customer and the platforms.

Alfredo C. Tan, Industry Professor, DeGroote School of Business at McMaster University has extensive experience on B2C advertising platforms, and understands the need for fair exchange, baked in trust:

If there was better control and understanding of how personal data is being used, I believe people would be willing to be more open. The balance is ensuring there is a fair value exchange taking place. In exchange for my data, my experiences become better, if not in the present but in the future. And as long as this is a trusted relationship, and people understand the value exchange then people are open to sharing more and more information. I am happy that Facebook, Amazon, and other platforms are aware that I am a male between 35–45 with specific interests in travel and pets, but no interest in hockey or skateboarding. Or that based on certain movies I watch, Netflix makes recommendation on what other types of content I would be interested in to keep me more entertained. And maybe that data is used elsewhere, with my permission to make experiences better on other platforms. The battle for data in an increasingly competitive consumer landscape is to increase engagement using personalized insight they have gleaned about their customers to ultimately create better experiences. I am certain many people do not want to go back to the anonymous web where all of us are treated largely the same and there was no differentiation in the experience.

Everyone agrees the regression to anonymity is not plausible nor tenable.

Privacy, Security, Trust and Sustainability

This is the future and it’s critical that business and government develop a stance and embrace a different way of thinking. As AI becomes more pervasive, the black box of algorithms will mandate business to develop systems and policies to be vigilant against the potential harms. Cavoukian understands it’s an uphill battle:

When I have these conversations with CEOs, at first they think I’m anti-business and all I want to do is shut them down. It’s the farthest thing from my mind. You have to have businesses operating in a way that will attract customers AND keep their business models operating. That’s the view I think you should take. It has to be a win/win for all parties.

Do you have a data map? I always start there. You need to map how the data flows throughout your organization and determine where you need additional consent. Follow the flow within your organization. This will identify any gaps that may need fixing.

TRUST: it takes years to build… and days to lose…

Perhaps this is the view that companies should take. Ann Cavoukian maintains that those who have implemented PbD say it builds enormous trust. When you have a trusted business relationship with your customers, they’re happy to give you additional consent down the road. They just don’t want the information flowing out to third parties unknown.

I tell companies if you do PbD, shout it from the rooftops. Lead with it. Tell your customers the lengths you’re going to to protect their privacy, and the respect you have for them. They will thank you in so many ways. You’ll gain their continued loyalty, and you’ll attract new opportunity.
I say to companies who see privacy as a negative, saying that it stifles creativity and innovation: ‘It’s the exact opposite: Privacy breeds innovation and prosperity, and it will give you a competitive advantage. It allows you to start with a base of trust, which steadily enhances the growth of your customers and their loyalty. Make it a win/win proposition!

Ann Cavoukian has recently launched Global Privacy and Security by Design: GPSbyDesign.org, an International Council on Global Privacy and Security. For more information on Ann Cavoukian, please go to Privacy by Design Centre of Excellence, at Ryerson University.

This article first appeared on Forbes: Part 1 and Part II.

Hessie Jones is the Founder of ArCompany advocating AI readiness, education and the ethical distribution of AI. She is also Cofounder of Salsa AI, distributing AI to the masses. As a seasoned digital strategist, author, tech geek and data junkie, she has spent the last 18 years on the internet at Yahoo!, Aegis Media, CIBC, and Citi, as well as tech startups including Cerebri, OverlayTV and Jugnoo. Hessie saw things change rapidly when search and social started to change the game for advertising and decided to figure out the way new market dynamics would change corporate environments forever: in process, in culture and in mindset. She launched her own business, ArCompany in social intelligence, and now, AI readiness. Through the weekly think tank discussions her team curated, she surfaced the generational divide in this changing technology landscape across a multitude of topics. Hessie is also a regular contributor to Towards Data Science on Medium and Cognitive World publications.

This article solely represents my views and in no way reflects those of DXJournal. Please feel free to contact me h.jones@arcompany.co

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Manufacturing

Tesla wants its factory workers to wear futuristic augmented reality glasses on the assembly line

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  • Tesla patent filings reveal plans for augmented reality glasses to assist with manufacturing.
  • Factory employees has previously used Google Glass in its factory as recently as 2016.

Tesla‘s Model 3 might have “biblical simplicity” according to one Wall Street analyst, but building any car still involves hundreds of nuts, bolts, and welds.

To cut down on the number of fit and finish issues — like the “significant inconsistencies” found by UBS— Tesla employees on the assembly line could soon use augmented reality glasses similar to Google Glass to help with car production, according to new patent filings.

Last week, Tesla filed two augmented reality patents that outline a futuristic vision for the relationship between humans and robots when it comes to manufacturing. The “smart glasses” would double as safety glasses, and would help workers identify places for joints, spot welds, and more, the filings say.

Here’s how it works:

Tesla/USPTO

And here’s the specific technical jargon outlining the invention (emphasis ours):

The AR device captures a live view of an object of interest, for example, a view of one or more automotive parts. The AR device determines the location of the device as well as the location and type of the object of interest. For example, the AR device identifies that the object of interest is a right hand front shock tower of a vehicle. The AR device then overlays data corresponding to features of the object of interest, such as mechanical joints, interfaces with other parts, thickness of e-coating, etc. on top of the view of the object of interest. Examples of the joint features include spot welds, self-pierced rivets, laser welds, structural adhesive, and sealers, among others. As the user moves around the object, the view of the object from the perspective of the AR device and the overlaid data of the detected features adjust accordingly.

As Electrek points out, Tesla has previously been employing Google Glass Enterprise as early as 2016, though it’s not clear how long it was in use.

Tesla has a tricky relationship with robotics in its factory. In April, CEO Elon Musk admitted its Fremont, California factory had relied too heavily on automated processes. Those comments, to CBS This Morning, came after criticism from a Bernstein analyst who said “We believe Tesla has been too ambitious with automation on the Model 3 line.”

Still, the company seems to be hoping for a more harmonious relationship between human and machine this time around.

“Applying computer vision and augmented reality tools to the manufacturing process can significantly increase the speed and efficiency related to manufacturing and in particular to the manufacturing of automobile parts and vehicles,” the patent application reads.

 

This article was originally published on Business Insider. Copyright 2018.

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Leadership

The great buy-in: How to learn to love AI at work

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Zoom.ai
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The conversation around AI is changing — and the emphasis on the augmentation of current workers, rather than the wholesale replacement of segments of the workforce, is a significant (and many would argue, necessary) shift. However, anxiety and fear are still tough contenders for those trying to usher in a new era of AI-assisted workplaces.

“It all comes down to what people want to change,” said Matas Sriubiskis, Growth Analyst at Zoom.ai, during the recent mesh conference meetup at Spaces in downtown Toronto.

Zoom.ai is a chat-based productivity tool that helps employees automate everyday tasks including searching for files, scheduling meetings, and generating documents. In an interview with DX JournalSriubiskis said public opposition to AI remains a major stumbling block not just for technology companies, but for businesses around the world.

As the language around AI changes, it becomes obvious that people want change from the technology, but remain hesitant about the disruptive effect AI-based automation could bring to their industries.

As highlighted in a recent Forbes article, knowledge-based workers with tenure, who have developed their skill-set over a period of time, are acting along the lines of basic psychology when it comes to fear surrounding automation. Unfortunately, that push-back can severely stunt the success of digital transformation projects designed to improve the lives of workers throughout the company, not replace them.

“A lot of people are afraid that AI’s going to take their job away,” said Sriubiskis. “That’s because that’s the narrative that we’ve seen for so long. It’s now about shifting the narrative to: AI’s going to make your job better and give you more time to focus more on the things that you’ve been hired to do because you’re good at doing them. There are tons of websites online talking about whether your job’s going to be taken away by AI, but they never really talk about how people’s jobs are going to be improved and what things they won’t have to do anymore so they can focus on the things that actually matter.”

Buy-in requires tangible results

This general AI anxiety can seem like a big obstacle to companies looking to adopt AI — but there are important steps companies can take to ensure their AI on-boarding is done with greater understanding and effectiveness.

As startups and businesses look to break through the AI fear-mongering, they have to demonstrate measurable benefits to employees, showing how AI can make work easier. By building an understanding of how AI affects employees, showing them how it benefits them, and using that information to inspire confidence in the project, businesses can work to create a higher level of employee buy-in.

One of the simplest examples of how to demonstrate this kind of benefit comes from Zoom.ai’s digital assistant for the workplace. An immediately beneficial way AI can augment knowledge-based workers is by giving them back their time.According to McKinsey & Company research cited by Zoom.ai, knowledge workers spend 19 percent of their time — one day a week — searching for and gathering information, sequestered by app or database silos. By showing how the employee experience can be improved with the use of automated meeting scheduling or document retrieval, you generate employee buy-in, said Sriubiskis.

“For us, the greatest advantage is giving employees some of their time back, so they can be more effective in the role that they were hired to do. So if there’s a knowledge-based worker, and they’re an engineer for example, they shouldn’t be spending time booking meetings, generating documents, finding information or submitting IT tickets. Their time would be better spent putting it towards their engineering work. For an enterprise company, based on our cases, we estimate that we can give employees at least 10 hours back a month. That allows them to be more productive, increase their collaboration and their creativity, and the overall employee experience improves.”

Full comprehension of a problem leads to better implementation

Another way to ensure a greater level of employee confidence is to understand the core problem that AI could be used to solve. You can’t just throw AI at an issue, said Sriubiskis. The application of the AI solution has to make sense in the context of an identified problem.

“When a lot of companies talk about their current endeavours, they’re saying, ‘we’re exploring AI to do this.’ But they’re not actually understanding a core problem that their employees are facing. If you just try to throw a new technology at a problem you don’t fully understand, you’re not going to be as successful as you want. You might be disappointed in that solution, and people are going to be frustrated that they wasted time without seeing any results.”

This deliberate effort to understand a key problem before implementing a solution can drive to better outcomes. That’s why Zoom.ai has incorporated this kind of core observation into its process of on-boarding clients or approaching a new project.

“Before we do a proof-of-concept or a pilot now,” said Sriubiskis, “we require companies to do an interview with some of our product and our UI/UX team. That way, we can understand how they do things currently, but also so we can provide a quantitative metric. Qualitative is nice, but people also want to see the results, and make sure their work was worth it. We  make sure to interview a whole bunch of users, clearly understand the problem, and make sure what we’re doing isn’t a barrier to what they’re actually trying to solve, it’s going to help it and help it more over time.”

These approaches are all about making the team of employees feel like an AI solution is working for them, leading to greater effectiveness of AI implementation to augment the workforce. It remains key, said Sriubiskis, to make sure employees can see the tangible benefits of the technology. Zoom.ai makes that employee experience a core part of their on-boarding process: “We report back to our users and tell them how many hours they’ve saved. So they see how the actual improvements are seen by them, not just by management or the company as a whole.”

The future is filled with AI. It’s just a question of making sure it helps, not hurts, human capital — and that a positive transition to AI tools prioritizes the employee experience along the way.

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Navigating the AI Hype

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Welcome to Navigating the AI Hype. This will be a timely article that curates events in AI to tabulate AI’s journey as this unprecedented phenomenon makes its way into our lives: The Good, the Bad and the Ugly. We will acknowledge successes in AI as well as those that still require further progress. We will also highlight areas where human conscience will need to dictate policy and regulation as ethical standards will be built in lockstep with technology as it evolves. Finally, we will highlight references and resources for anyone wanting to dive in further into Artificial Intelligence. Enjoy!

The Good:

DeepMind AlphaFold Delivers “Unprecedented Progress” on Protein Folding

“Proteins are essential to life. Predicting their 3D structure is a major unsolved challenge in biology and could impact disease understanding and drug discovery. I’m excited to announce that we have won the CASP13 protein folding competition!”

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Facebook And MIT Researchers Want To Use AI To Create Addresses For The Billions Of People Who Don’t Have One

“Artificial intelligence will revolutionize how we live, creating both incredible opportunity for benefits, as well as some disruption that will be important to manage,”

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The Bad:

Tech giants offer empty apologies because users can’t quit

“Sorry means nothing since so does We’re deleting.”.

Read more.

 

DuckDuckGo Says Google’s Filter Bubble Is Real, and It Can Prove It

A study shows incognito mode does not mean anonymous

Read more.

 

Microsoft President: We’ll Give Pentagon ‘All the Technology We Create’

“For us, we’ve been clear: we are gonna provide the US military with access to the best technology — to all the technology — we create. Full stop. We just said that flat out.”

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The Ugly:

LinkedIn used 18M non-member emails to target Facebook ads. Were you a victim?

A Data Protection Commissioner investigation found that LinkedIn violated data protection policies shortly before onset of GDPR

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Marriott hotels: data of 500m guests may have been exposed

“This indicates that as far as security monitoring and being able to respond in a timely and adequate fashion, Marriott had severe challenges being able to live up to its mission statement of keeping customer data safe.”

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Quora data breach FAQ: What 100 million hacked users need to know

“On Friday [November 30] we discovered that some user data was compromised by a third party who gained unauthorized access to one of our systems.” 

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Emails of top NRCC officials stolen in major 2018 hack

“The NRCC can confirm that it was the victim of a cyber intrusion by an unknown entity. The cybersecurity of the Committee’s data is paramount, and upon learning of the intrusion, the NRCC immediately launched an internal investigation and notified the FBI, which is now investigating the matter,”

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AI courses and resources

NO TIME TO READ AI RESEARCH? WE SUMMARIZED TOP 2018 PAPERS FOR YOU

H2O.ai Resources 

Deep Learning Resources

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