Opinion: Accountability and AI
With right manoeuvres, responsible entrepreneurship and AI can be a perfect pair and empower development
By Viiveck Verma
Business in the age of artificial intelligence (AI) is not the same as before. From facilitating a search on the internet to preparing entire spreadsheets to writing reports, AI has taken over many aspects of everyday work in the domain of business. Its importance has been recognised by the stakeholders as well, with a huge number of businesses declaring AI as part of their core strategic models and AI accounting for a major percentage of venture capital investments worldwide, as reported by several publications.
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In this context, the way we perceive entrepreneurship, or running a business enterprise, and more importantly, responsible entrepreneurship, has undergone a paradigm shift. By pushing the envelope on productivity and taking it beyond human limitations, AI has introduced new avenues for the creation of value as well as new challenges for ethical and responsible business. What does responsible entrepreneurship look like in the age of AI? Let us analyse.
Bundle of Concerns
At its heart, responsible entrepreneurship is all about being accountable and committed to goals, actions and stakeholders. Often, this involves keeping social and environmental concerns in mind, examples being, mitigating the socioeconomic vulnerabilities of people who work for you by knowing them well, paying them fairly and giving them the flexibility to decide to work remotely, if necessary. With AI coming into play, responsibility gets complicated. How are we supposed to ensure that workers are able to seamlessly operate with the newest technological developments all the time? How do we ensure data security and maintain your credibility? How do we interpret the insights gleaned by AI when that was the work of seasoned experts? This bundle of concerns merits addressing.
First of all, let us begin with the question of credibility and dependability. While AI has definitely made things quick and easy, the ease is manufactured out of huge databases and programming. Therefore, the loss of privacy is a major concern in this context. Since AI systems frequently rely on enormous amounts of data, this phenomenon raises several questions about data privacy. Similarly, integrating AI into the extant business models can cause gaps, disruptions and lapses, which can lead to difficulties. For instance, if consumer feedback was kept by a certain individual earlier and the company has installed a software for the same now, the feedback collected in the interim period, the phase of transition between the old and the new regime might be difficult to trace later, for confusions can run amok, leading to loss of information.
Secondly, the question of relevant skill sets and appropriate specialisations for employees and constant training is important. This is because, with relentless updates and developments, employees have to be trained relentlessly to attune them to AI. Not only can this be a challenge but can also be labelled unfair by workers who had been hired based on a certain skill set. Moreover, there is a need to diversify specialised teams when AI comes into play because it involves legal and social dimensions as well. As a result, teams with legal expertise are required to navigate the intricate web of laws and regulations pertaining to Al.
Thirdly, the popular perception of AI remains a roadblock to its widespread acceptance and adoption by people. Not only can customers find interaction with human agents more reassuring and trustworthy, but the possibility of AI upending structures of employment and taking jobs away also remains a prominent anxiety in the public consciousness. Employees fear being displaced and reduced to redundant positions if not being unemployed. Since responsible business involves the trust of stakeholders, these aspects of the presence of AI pose difficulties to the prospect of carrying out ethical and dependable business.
One at a Time
Responsible entrepreneurship, therefore, requires preparedness to deal with these problems. Instead of getting flabbergasted at the surfeit of issues, handling them one at a time is the way out. For instance, to ensure data security, strong data protection measures, such as anonymising, encrypting and responsibly storing user data, must be given top priority by all business owners. Building user trust is crucial because companies need to be open about how they use their data and get people’s informed consent.
For the legal aspect, entrepreneurs are required to deploy their resources, particularly time and money, in hiring legal counsel to comply with data protection laws, intellectual property regulations and industry-specific standards. Employees can be trained in a more holistic and academic way at once, rather than through irregular workshops so that every development in AI merely seems like an accessible and comprehensible software update. In a similar vein, both employees and customers can be sensitised to the benefits of AI while telling them the whys and the hows behind its adoption in particular cases.
Involving Humans
Most importantly, however, AI must be used under human supervision with no part of the process being completely surrendered to it. The work done by AI must be monitored and assessed by human experts. The teams can continue to work for the aims they were recruited for, with a shift in workload from rudimentary to advanced goals, with AI taking care of the former with its work being ratified by the team members. AI, therefore, has to be used as a tool to simplify daily challenges rather than as a way to replace skilled performers. This integrated operational model can foster and consolidate the credibility of AI-powered entrepreneurship.
On the whole, accountable and responsible entrepreneurship in the age of AI necessitates a comprehensive and holistic strategy with a problem-solving outlook at the forefront. To ensure fairness, transparency and accountability in Al systems, entrepreneurs must consider ethical issues and simultaneously promote trust through conversations with stakeholders, facilitating reskilling initiatives to support the workforce.
Last but not least, it’s crucial to comprehend the regulatory landscape, which calls for active interaction with decision-makers, legal authorities and the industry at large. With the right manoeuvres, responsible entrepreneurship and AI can be a perfect pair, and it is incumbent upon us to create avenues for such empowering developments.
